Paper Title Sanity Check

From d97107ed5b242a3913df0d88ef4d8374b66ca25c Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 12 Feb 2019 19:21:29 +0100 Subject: begin geocode client --- scraper/s2-geocode-server.py | 54 ++++++++++++++++++++++++++++++++++++++++++++ 1 file changed, 54 insertions(+) create mode 100644 scraper/s2-geocode-server.py (limited to 'scraper/s2-geocode-server.py') diff --git a/scraper/s2-geocode-server.py b/scraper/s2-geocode-server.py new file mode 100644 index 00000000..021921fe --- /dev/null +++ b/scraper/s2-geocode-server.py @@ -0,0 +1,54 @@ +#!python + +import os +import sys +import json +import time +import argparse +from datetime import datetime +from flask import Flask, request, render_template, jsonify + +from dotenv import load_dotenv +load_dotenv() + +from util import * + +app = Flask(__name__, static_url_path="/reports/", static_folder="reports") + +# static api route +@app.route('/', methods=['GET']) +def index(): + return app.send_static_file('reports/geocode-papers.html') + +# route to list the papers +# route to get all the un-geocoded citations for a paper +# route to get all the manually geocoded IDs (to dedupe) +# route to add a geocoding for a paper + +@app.route('/api/institutions', methods=['GET']) +def list_locations(): + addresses = AddressBook() + return jsonify({ + 'entities': addresses.entities, + 'lookup': addresses.lookup, + }) + +@app.route('/api/papers', methods=['GET']) +def list_papers(): + lookup_keys, lines = fetch_google_sheet('citation_lookup') + lookup = {} + for line in lines: + lookup[line[0]] = line + return jsonify({ + 'papers': papers, + }) + +@app.route('/api/papers/:citation/', methods=['GET']) +def list_citations(citation): + return jsonify({ + }) + +@app.route('/api/geocode', methods=['POST']) +def geocode_paper(): + return jsonify({ + }) -- cgit v1.2.3-70-g09d2 From 63133aa1bda1ef101772b1d85e27b8d320d32412 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 12 Feb 2019 22:34:19 +0100 Subject: re-running reports.. --- scraper/reports/paper_title_report.html | 4 ++-- scraper/reports/paper_title_report_no_location.html | 4 ++-- scraper/reports/paper_title_report_nonmatching.html | 4 ++-- scraper/s2-final-report.py | 2 ++ scraper/s2-geocode-server.py | 4 ++++ scraper/s2-papers.py | 4 ++++ scraper/util.py | 4 ++-- 7 files changed, 18 insertions(+), 8 deletions(-) (limited to 'scraper/s2-geocode-server.py') diff --git a/scraper/reports/paper_title_report.html b/scraper/reports/paper_title_report.html index adfec23b..90deaf36 100644 --- a/scraper/reports/paper_title_report.html +++ b/scraper/reports/paper_title_report.html @@ -1,3 +1,3 @@ -Paper Title Sanity Check

Paper Title Sanity Check

key

name

our title

found title

address

s2 id

10k_US_adult_faces

10K US Adult Faces

The intrinsic memorability of face images

The intrinsic memorability of face photographs.

[pdf]

[s2]

8b2dd5c61b23ead5ae5508bb8ce808b5ea266730

3d_rma

3D-RMA

Automatic 3D Face Authentication

Automatic 3D face authentication

[pdf]

[s2]

2160788824c4c29ffe213b2cbeb3f52972d73f37

3dddb_unconstrained

3D Dynamic

A 3D Dynamic Database for Unconstrained Face Recognition

A 3 D Dynamic Database for Unconstrained Face Recognition

[pdf]

[s2]

4d4bb462c9f1d4e4ab1e4aa6a75cc0bc71b38461

3dpes

3DPeS

3DPes: 3D People Dataset for Surveillance and Forensics

3DPeS: 3D people dataset for surveillance and forensics

[pdf]

[s2]

2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e

4dfab

4DFAB

4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications

[pdf]

[s2]

9696ad8b164f5e10fcfe23aacf74bd6168aebb15

50_people_one_question

50 People One Question

Merging Pose Estimates Across Space and Time

[pdf]

[s2]

5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725

a_pascal_yahoo

aPascal

Describing Objects by their Attributes

Describing objects by their attributes

[pdf]

[s2]

2e384f057211426ac5922f1b33d2aa8df5d51f57

adience

Adience

Age and Gender Estimation of Unfiltered Faces

[pdf]

[s2]

1be498d4bbc30c3bfd0029114c784bc2114d67c0

afad

AFAD

Ordinal Regression with a Multiple Output CNN for Age Estimation

Ordinal Regression with Multiple Output CNN for Age Estimation

[pdf]

[s2]

6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c

afew_va

AFEW-VA

AFEW-VA database for valence and arousal estimation in-the-wild

[pdf]

[s2]

2624d84503bc2f8e190e061c5480b6aa4d89277a

afew_va

AFEW-VA

Collecting Large, Richly Annotated Facial-Expression Databases from Movies

[pdf]

[s2]

Australian National University

b1f4423c227fa37b9680787be38857069247a307

affectnet

AffectNet

AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild

[pdf]

[s2]

758d7e1be64cc668c59ef33ba8882c8597406e53

aflw

AFLW

Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

afw

AFW

Face detection, pose estimation and landmark localization in the wild

Face detection, pose estimation, and landmark localization in the wild

[pdf]

[s2]

University of California, Irvine

0e986f51fe45b00633de9fd0c94d082d2be51406

agedb

AgeDB

AgeDB: the first manually collected, in-the-wild age database

AgeDB: The First Manually Collected, In-the-Wild Age Database

[pdf]

[s2]

6dcf418c778f528b5792104760f1fbfe90c6dd6a

alert_airport

ALERT Airport

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.

[pdf]

[s2]

6403117f9c005ae81f1e8e6d1302f4a045e3d99d

am_fed

AM-FED

Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”

Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"

[pdf]

[s2]

47aeb3b82f54b5ae8142b4bdda7b614433e69b9a

apis

APiS1.0

Pedestrian Attribute Classification in Surveillance: Database and Evaluation

[pdf]

[s2]

488e475eeb3bb39a145f23ede197cd3620f1d98a

ar_facedb

AR Face

The AR Face Database

The AR face database

[pdf]

[s2]

6d96f946aaabc734af7fe3fc4454cf8547fcd5ed

awe_ears

AWE Ears

Ear Recognition: More Than a Survey

[pdf]

[s2]

84fe5b4ac805af63206012d29523a1e033bc827e

b3d_ac

B3D(AC)

A 3-D Audio-Visual Corpus of Affective Communication

[pdf]

[s2]

d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae

bbc_pose

BBC Pose

Automatic and Efficient Human Pose Estimation for Sign Language Videos

[pdf]

[s2]

213a579af9e4f57f071b884aa872651372b661fd

berkeley_pose

BPAD

Describing People: A Poselet-Based Approach to Attribute Classification

Describing people: A poselet-based approach to attribute classification

[pdf]

[s2]

7808937b46acad36e43c30ae4e9f3fd57462853d

bfm

BFM

A 3D Face Model for Pose and Illumination Invariant Face Recognition

[pdf]

[s2]

639937b3a1b8bded3f7e9a40e85bd3770016cf3c

bio_id

BioID Face

Robust Face Detection Using the Hausdorff Distance

[pdf]

[s2]

4053e3423fb70ad9140ca89351df49675197196a

bjut_3d

BJUT-3D

The BJUT-3D Large-Scale Chinese Face Database

A novel face recognition method based on 3D face model

[pdf]

[s2]

1ed1a49534ad8dd00f81939449f6389cfbc25321

bosphorus

The Bosphorus

Bosphorus Database for 3D Face Analysis

[pdf]

[s2]

2acf7e58f0a526b957be2099c10aab693f795973

bp4d_plus

BP4D+

Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis

[pdf]

[s2]

53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4

bp4d_spontanous

BP4D-Spontanous

A high resolution spontaneous 3D dynamic facial expression database

A high-resolution spontaneous 3D dynamic facial expression database

[pdf]

[s2]

SUNY Binghamton

b91f54e1581fbbf60392364323d00a0cd43e493c

brainwash

Brainwash

Brainwash dataset

Brainwash: A Data System for Feature Engineering

[pdf]

[s2]

214c966d1f9c2a4b66f4535d9a0d4078e63a5867

bu_3dfe

BU-3DFE

A 3D Facial Expression Database For Facial Behavior Research

A 3D facial expression database for facial behavior research

[pdf]

[s2]

SUNY Binghamton

cc589c499dcf323fe4a143bbef0074c3e31f9b60

buhmap_db

BUHMAP-DB

Facial Feature Tracking and Expression Recognition for Sign Language

Facial feature tracking and expression recognition for sign language

[pdf]

[s2]

014b8df0180f33b9fea98f34ae611c6447d761d2

cafe

CAFE

The Child Affective Facial Expression (CAFE) Set: Validity and reliability from untrained adults

The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults

[pdf]

[s2]

20388099cc415c772926e47bcbbe554e133343d1

caltech_10k_web_faces

Caltech 10K Web Faces

Pruning Training Sets for Learning of Object Categories

Pruning training sets for learning of object categories

[pdf]

[s2]

636b8ffc09b1b23ff714ac8350bb35635e49fa3c

caltech_pedestrians

Caltech Pedestrians

Pedestrian Detection: A Benchmark

Pedestrian detection: A benchmark

[pdf]

[s2]

1dc35905a1deff8bc74688f2d7e2f48fd2273275

caltech_pedestrians

Caltech Pedestrians

Pedestrian Detection: An Evaluation of the State of the Art

[pdf]

[s2]

f72f6a45ee240cc99296a287ff725aaa7e7ebb35

camel

CAMEL

CAMEL Dataset for Visual and Thermal Infrared Multiple Object Detection and Tracking

Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

[pdf]

[s2]

5801690199c1917fa58c35c3dead177c0b8f9f2d

cas_peal

CAS-PEAL

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

[pdf]

[s2]

2485c98aa44131d1a2f7d1355b1e372f2bb148ad

casablanca

Casablanca

Context-aware {CNNs} for person head detection

Context-Aware CNNs for Person Head Detection

[pdf]

[s2]

0ceda9dae8b9f322df65ca2ef02caca9758aec6f

casia_webface

CASIA Webface

Learning Face Representation from Scratch

[pdf]

[s2]

853bd61bc48a431b9b1c7cab10c603830c488e39

celeba

CelebA

Deep Learning Face Attributes in the Wild

[pdf]

[s2]

Chinese University of Hong Kong

6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4

celeba_plus

CelebFaces+

Deep Learning Face Representation from Predicting 10,000 Classes

[pdf]

[s2]

Shenzhen Institutes of Advanced Technology

177bc509dd0c7b8d388bb47403f28d6228c14b5c

cfd

CFD

The Chicago face database: A free stimulus set of faces and norming data

The Chicago face database: A free stimulus set of faces and norming data.

[pdf]

[s2]

4df3143922bcdf7db78eb91e6b5359d6ada004d2

chalearn

ChaLearn

ChaLearn Looking at People: A Review of Events and Resources

ChaLearn looking at people: A review of events and resources

[pdf]

[s2]

8d5998cd984e7cce307da7d46f155f9db99c6590

chokepoint

ChokePoint

Patch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition

Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition

[pdf]

[s2]

University of Queensland

0486214fb58ee9a04edfe7d6a74c6d0f661a7668

cityscapes

Cityscapes

The Cityscapes Dataset for Semantic Urban Scene Understanding

[pdf]

[s2]

32cde90437ab5a70cf003ea36f66f2de0e24b3ab

cityscapes

Cityscapes

The Cityscapes Dataset

[pdf]

[s2]

5ffd74d2873b7cba2cbc5fd295cc7fbdedca22a2

clothing_co_parsing

CCP

Clothing Co-Parsing by Joint Image Segmentation and Labeling

Clothing Co-parsing by Joint Image Segmentation and Labeling

[pdf]

[s2]

2bf8541199728262f78d4dced6fb91479b39b738

cmdp

CMDP

Distance Estimation of an Unknown Person from a Portrait

[pdf]

[s2]

California Institute of Technology

56ae6d94fc6097ec4ca861f0daa87941d1c10b70

cmu_pie

CMU PIE

The CMU Pose, Illumination, and Expression Database

The CMU Pose, Illumination, and Expression (PIE) Database

[pdf]

[s2]

4d423acc78273b75134e2afd1777ba6d3a398973

coco

COCO

Microsoft COCO: Common Objects in Context

[pdf]

[s2]

5e0f8c355a37a5a89351c02f174e7a5ddcb98683

coco_action

COCO-a

Describing Common Human Visual Actions in Images

[pdf]

[s2]

4946ba10a4d5a7d0a38372f23e6622bd347ae273

coco_qa

COCO QA

Exploring Models and Data for Image Question Answering

[pdf]

[s2]

35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62

cofw

COFW

Robust face landmark estimation under occlusion

Robust Face Landmark Estimation under Occlusion

[pdf]

[s2]

2724ba85ec4a66de18da33925e537f3902f21249

cohn_kanade

Comprehensive Database for Facial Expression Analysis

[pdf]

[s2]

Carnegie Mellon University

23fc83c8cfff14a16df7ca497661264fc54ed746

cohn_kanade_plus

CK+

The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression

[pdf]

[s2]

4d9a02d080636e9666c4d1cc438b9893391ec6c7

columbia_gaze

Columbia Gaze

Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction

Gaze locking: passive eye contact detection for human-object interaction

[pdf]

[s2]

06f02199690961ba52997cde1527e714d2b3bf8f

complex_activities

Ongoing Complex Activities

Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space

Recognition of ongoing complex activities by sequence prediction over a hierarchical label space

[pdf]

[s2]

65355cbb581a219bd7461d48b3afd115263ea760

cuhk01

CUHK01

Human Reidentification with Transferred Metric Learning

[pdf]

[s2]

44484d2866f222bbb9b6b0870890f9eea1ffb2d0

cuhk02

CUHK02

Locally Aligned Feature Transforms across Views

[pdf]

[s2]

38b55d95189c5e69cf4ab45098a48fba407609b4

cuhk03

CUHK03

DeepReID: Deep Filter Pairing Neural Network for Person Re-identification

[pdf]

[s2]

6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3

cvc_01_barcelona

CVC-01

Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection

Adaptive Image Sampling and Windows Classification for On – board Pedestrian Detection

[pdf]

[s2]

57fe081950f21ca03b5b375ae3e84b399c015861

czech_news_agency

UFI

Unconstrained Facial Images: Database for Face Recognition under Real-world Conditions

Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions

[pdf]

[s2]

4b4106614c1d553365bad75d7866bff0de6056ed

d3dfacs

D3DFACS

A FACS Valid 3D Dynamic Action Unit database with Applications to 3D Dynamic Morphable Facial Modelling

A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling

[pdf]

[s2]

Jacobs University

070de852bc6eb275d7ca3a9cdde8f6be8795d1a3

dartmouth_children

Dartmouth Children

The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set

The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set

[pdf]

[s2]

4e6ee936eb50dd032f7138702fa39b7c18ee8907

data_61

Data61 Pedestrian

A Multi-Modal Graphical Model for Scene Analysis

A Multi-modal Graphical Model for Scene Analysis

[pdf]

[s2]

563c940054e4b456661762c1ab858e6f730c3159

deep_fashion

DeepFashion

DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations

[pdf]

[s2]

18010284894ed0edcca74e5bf768ee2e15ef7841

deep_fashion

DeepFashion

Fashion Landmark Detection in the Wild

[pdf]

[s2]

Chinese University of Hong Kong

4fefd1bc8dc4e0ab37ee3324ddfa43ad9d6a04a7

disfa

DISFA

DISFA: A Spontaneous Facial Action Intensity Database

Extended DISFA Dataset: Investigating Posed and Spontaneous Facial Expressions

[pdf]

[s2]

a5acda0e8c0937bfed013e6382da127103e41395

distance_nighttime

Long Distance Heterogeneous Face

Nighttime Face Recognition at Long Distance: Cross-distance and Cross-spectral Matching

Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching

[pdf]

[s2]

4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06

duke_mtmc

Duke MTMC

Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking

[pdf]

[s2]

27a2fad58dd8727e280f97036e0d2bc55ef5424c

emotio_net

EmotioNet Database

EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild

[pdf]

[s2]

c900e0ad4c95948baaf0acd8449fde26f9b4952a

eth_andreas_ess

ETHZ Pedestrian

Depth and Appearance for Mobile Scene Analysis

[pdf]

[s2]

13f06b08f371ba8b5d31c3e288b4deb61335b462

europersons

EuroCity Persons

The EuroCity Persons Dataset: A Novel Benchmark for Object Detection

[pdf]

[s2]

f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4

expw

ExpW

Learning Social Relation Traits from Face Images

[pdf]

[s2]

Chinese University of Hong Kong

2a171f8d14b6b8735001a11c217af9587d095848

expw

ExpW

From Facial Expression Recognition to Interpersonal Relation Prediction

[pdf]

[s2]

22f656d0f8426c84a33a267977f511f127bfd7f3

face_research_lab

Face Research Lab London

Face Research Lab London Set. figshare

Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.

[pdf]

[s2]

University College London

c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8

face_scrub

FaceScrub

A data-driven approach to cleaning large face datasets

[pdf]

[s2]

University of Illinois, Urbana-Champaign

0d3bb75852098b25d90f31d2f48fd0cb4944702b

face_tracer

FaceTracer

FaceTracer: A Search Engine for Large Collections of Images with Faces

[pdf]

[s2]

Columbia University

4c170a0dcc8de75587dae21ca508dab2f9343974

face_tracer

FaceTracer

Face Swapping: Automatically Replacing Faces in Photographs

Face swapping: automatically replacing faces in photographs

[pdf]

[s2]

Columbia University

670637d0303a863c1548d5b19f705860a23e285c

facebook_100

Facebook100

Scaling Up Biologically-Inspired Computer Vision: A Case Study in Unconstrained Face Recognition on Facebook

Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook

[pdf]

[s2]

Harvard University

9c23859ec7313f2e756a3e85575735e0c52249f4

faceplace

Face Place

Recognizing disguised faces

[pdf]

[s2]

25474c21613607f6bb7687a281d5f9d4ffa1f9f3

families_in_the_wild

FIW

Visual Kinship Recognition of Families in the Wild

[pdf]

[s2]

dd65f71dac86e36eecbd3ed225d016c3336b4a13

fddb

FDDB

FDDB: A Benchmark for Face Detection in Unconstrained Settings

A Benchmark for Face Detection in Unconstrained Settings

[pdf]

[s2]

University of Massachusetts

75da1df4ed319926c544eefe17ec8d720feef8c0

fei

FEI

Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro

Generalização cartográfica automatizada para um banco de dados cadastral

[pdf]

[s2]

b6b1b0632eb9d4ab1427278f5e5c46f97753c73d

feret

FERET

The FERET Verification Testing Protocol for Face Recognition Algorithms

[pdf]

[s2]

0c4a139bb87c6743c7905b29a3cfec27a5130652

feret

FERET

The FERET database and evaluation procedure for face-recognition algorithms

[pdf]

[s2]

dc8b25e35a3acb812beb499844734081722319b4

feret

FERET

FERET ( Face Recognition Technology ) Recognition Algorithm Development and Test Results

[pdf]

[s2]

31de9b3dd6106ce6eec9a35991b2b9083395fd0b

feret

FERET

The FERET Evaluation Methodology for Face-Recognition Algorithms

[pdf]

[s2]

0f0fcf041559703998abf310e56f8a2f90ee6f21

ferplus

FER+

Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution

Training deep networks for facial expression recognition with crowd-sourced label distribution

[pdf]

[s2]

298cbc3dfbbb3a20af4eed97906650a4ea1c29e0

fia

CMU FiA

The CMU Face In Action (FIA) Database

[pdf]

[s2]

47662d1a368daf70ba70ef2d59eb6209f98b675d

fiw_300

300-W

300 faces In-the-wild challenge: Database and results

300 Faces In-The-Wild Challenge: database and results

[pdf]

[s2]

e4754afaa15b1b53e70743880484b8d0736990ff

fiw_300

300-W

300 Faces in-the-Wild Challenge: The first facial landmark localization Challenge

300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge

[pdf]

[s2]

University of Twente

044d9a8c61383312cdafbcc44b9d00d650b21c70

fiw_300

300-W

A semi-automatic methodology for facial landmark annotation

A Semi-automatic Methodology for Facial Landmark Annotation

[pdf]

[s2]

University of Twente

013909077ad843eb6df7a3e8e290cfd5575999d2

frav3d

FRAV3D

MULTIMODAL 2D, 2.5D & 3D FACE VERIFICATION

Multimodal 2D, 2.5D & 3D Face Verification

[pdf]

[s2]

2b926b3586399d028b46315d7d9fb9d879e4f79c

frgc

FRGC

Overview of the Face Recognition Grand Challenge

Overview of the face recognition grand challenge

[pdf]

[s2]

18ae7c9a4bbc832b8b14bc4122070d7939f5e00e

gallagher

Gallagher

Clothing Cosegmentation for Recognizing People

Clothing cosegmentation for recognizing people

[pdf]

[s2]

22ad2c8c0f4d6aa4328b38d894b814ec22579761

gavab_db

Gavab

GavabDB: a 3D face database

Expression invariant 3D face recognition with a Morphable Model

[pdf]

[s2]

42505464808dfb446f521fc6ff2cfeffd4d68ff1

geofaces

GeoFaces

GeoFaceExplorer: Exploring the Geo-Dependence of Facial Attributes

GeoFaceExplorer: exploring the geo-dependence of facial attributes

[pdf]

[s2]

University of Kentucky

17b46e2dad927836c689d6787ddb3387c6159ece

georgia_tech_face_database

Georgia Tech Face

Maximum likelihood training of the embedded HMM for face detection and recognition

MAXIMUM LIKELIHOOD TRAINING OF THE EMBEDDED HMM FOR FACE DETECTION AND RECOGNITION Ara V. Ne an and Monson H. Hayes III Center for Signal and Image Processing School of Electrical and Computer Engineering

[pdf]

[s2]

3dc3f0b64ef80f573e3a5f96e456e52ee980b877

graz

Graz Pedestrian

Generic Object Recognition with Boosting

Generic object recognition with boosting

[pdf]

[s2]

2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9

graz

Graz Pedestrian

Weak Hypotheses and Boosting for Generic Object Detection and Recognition

[pdf]

[s2]

0c91808994a250d7be332400a534a9291ca3b60e

graz

Graz Pedestrian

Object Recognition Using Segmentation for Feature Detection

Object recognition using segmentation for feature detection

[pdf]

[s2]

12ad3b5bbbf407f8e54ea692c07633d1a867c566

h3d

H3D

Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations

Poselets: Body part detectors trained using 3D human pose annotations

[pdf]

[s2]

2830fb5282de23d7784b4b4bc37065d27839a412

hda_plus

HDA+

The HDA+ data set for research on fully automated re-identification systems

The HDA+ Data Set for Research on Fully Automated Re-identification Systems

[pdf]

[s2]

8f02ec0be21461fbcedf51d864f944cfc42c875f

hda_plus

HDA+

A Multi-camera video data set for research on High-Definition surveillance

HDA dataset-DRAFT 1 A Multi-camera video data set for research on High-Definition surveillance

[pdf]

[s2]

bd88bb2e4f351352d88ee7375af834360e223498

helen

Helen

Interactive Facial Feature Localization

[pdf]

[s2]

University of Illinois, Urbana-Champaign

95f12d27c3b4914e0668a268360948bce92f7db3

hi4d_adsip

Hi4D-ADSIP

Hi4D-ADSIP 3-D dynamic facial articulation database

High-resolution comprehensive 3-D dynamic database for facial articulation analysis

[pdf]

[s2]

24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd

hipsterwars

Hipsterwars

Hipster Wars: Discovering Elements of Fashion Styles

[pdf]

[s2]

Tohoku University

04c2cda00e5536f4b1508cbd80041e9552880e67

hollywood_headset

HollywoodHeads

Context-aware CNNs for person head detection

Context-Aware CNNs for Person Head Detection

[pdf]

[s2]

0ceda9dae8b9f322df65ca2ef02caca9758aec6f

hrt_transgender

HRT Transgender

Is the Eye Region More Reliable Than the Face? A Preliminary Study of Face-based Recognition on a Transgender Dataset

Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset

[pdf]

[s2]

University of North Carolina Wilmington

137aa2f891d474fce1e7a1d1e9b3aefe21e22b34

hrt_transgender

HRT Transgender

Investigating the Periocular-Based Face Recognition Across Gender Transformation

[pdf]

[s2]

University of North Carolina at Wilmington

2f43b614607163abf41dfe5d17ef6749a1b61304

hrt_transgender

HRT Transgender

Face recognition across gender transformation using SVM Classifier

Face recognition: A literature survey

[pdf]

[s2]

28312c3a47c1be3a67365700744d3d6665b86f22

ifad

IFAD

Indian Face Age Database: A Database for Face Recognition with Age Variation

Indian Face Age Database : A Database for Face Recognition with Age Variation

[pdf]

[s2]

55c40cbcf49a0225e72d911d762c27bb1c2d14aa

ifdb

IFDB

Iranian Face Database with age, pose and expression

[pdf]

[s2]

b71d1aa90dcbe3638888725314c0d56640c1fef1

ifdb

IFDB

Iranian Face Database and Evaluation with a New Detection Algorithm

[pdf]

[s2]

066d71fcd997033dce4ca58df924397dfe0b5fd1

iit_dehli_ear

IIT Dehli Ear

Automated human identification using ear imaging

Automated Human Identification Using Ear Imaging

[pdf]

[s2]

faf40ce28857aedf183e193486f5b4b0a8c478a2

ijb_c

IJB-A

Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A

Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A

[pdf]

[s2]

140c95e53c619eac594d70f6369f518adfea12ef

ijb_c

IJB-B

IARPA Janus Benchmark-B Face Dataset

[pdf]

[s2]

0cb2dd5f178e3a297a0c33068961018659d0f443

ijb_c

IJB-C

IARPA Janus Benchmark C

IARPA Janus Benchmark - C: Face Dataset and Protocol

[pdf]

[s2]

57178b36c21fd7f4529ac6748614bb3374714e91

ilids_mcts

Imagery Library for Intelligent Detection Systems: The i-LIDS User Guide

Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems

[pdf]

[s2]

0297448f3ed948e136bb06ceff10eccb34e5bb77

ilids_vid_reid

iLIDS-VID

Person Re-Identication by Video Ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

images_of_groups

Images of Groups

Understanding Groups of Images of People

Understanding images of groups of people

[pdf]

[s2]

21d9d0deed16f0ad62a4865e9acf0686f4f15492

imdb_wiki

IMDB

Deep expectation of real and apparent age from a single image without facial landmarks

Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks

[pdf]

[s2]

10195a163ab6348eef37213a46f60a3d87f289c5

imdb_wiki

IMDB

DEX: Deep EXpectation of apparent age from a single image

DEX: Deep EXpectation of Apparent Age from a Single Image

[pdf]

[s2]

8355d095d3534ef511a9af68a3b2893339e3f96b

imfdb

IMFDB

Indian Movie Face Database: A Benchmark for Face Recognition Under Wide Variations

Indian Movie Face Database: A benchmark for face recognition under wide variations

[pdf]

[s2]

ca3e88d87e1344d076c964ea89d91a75c417f5ee

imm_face

IMM Face Dataset

The IMM Face Database - An Annotated Dataset of 240 Face Images

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

immediacy

Immediacy

Multi-task Recurrent Neural Network for Immediacy Prediction

[pdf]

[s2]

1e3df3ca8feab0b36fd293fe689f93bb2aaac591

imsitu

imSitu

Situation Recognition: Visual Semantic Role Labeling for Image Understanding

[pdf]

[s2]

University of Washington

51eba481dac6b229a7490f650dff7b17ce05df73

inria_person

INRIA Pedestrian

Histograms of Oriented Gradients for Human Detection

Histograms of oriented gradients for human detection

[pdf]

[s2]

10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5

jaffe

JAFFE

Coding Facial Expressions with Gabor Wavelets

[pdf]

[s2]

Kyushu University

45c31cde87258414f33412b3b12fc5bec7cb3ba9

jiku_mobile

Jiku Mobile Video Dataset

The Jiku Mobile Video Dataset

The jiku mobile video dataset

[pdf]

[s2]

d178cde92ab3dc0dd2ebee5a76a33d556c39448b

jpl_pose

JPL-Interaction dataset

First-Person Activity Recognition: What Are They Doing to Me?

[pdf]

[s2]

1aad2da473888cb7ebc1bfaa15bfa0f1502ce005

kdef

KDEF

The Karolinska Directed Emotional Faces – KDEF

Gaze fixation and the neural circuitry of face processing in autism

[pdf]

[s2]

93884e46c49f7ae1c7c34046fbc28882f2bd6341

kin_face

UB KinFace

Genealogical Face Recognition based on UB KinFace Database

Genealogical face recognition based on UB KinFace database

[pdf]

[s2]

SUNY Buffalo

2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d

kin_face

UB KinFace

Kinship Verification through Transfer Learning

[pdf]

[s2]

4793f11fbca4a7dba898b9fff68f70d868e2497c

kin_face

UB KinFace

Understanding Kin Relationships in a Photo

[pdf]

[s2]

08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7

kinectface

KinectFaceDB

KinectFaceDB: A Kinect Database for Face Recognition

[pdf]

[s2]

0b440695c822a8e35184fb2f60dcdaa8a6de84ae

kitti

KITTI

Vision meets Robotics: The KITTI Dataset

The Role of Machine Vision for Intelligent Vehicles

[pdf]

[s2]

35ba4ebfd017a56b51e967105af9ae273c9b0178

lag

LAG

Large Age-Gap Face Verification by Feature Injection in Deep Networks

Large age-gap face verification by feature injection in deep networks

[pdf]

[s2]

0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e

large_scale_person_search

Large Scale Person Search

End-to-End Deep Learning for Person Search

[pdf]

[s2]

2161f6b7ee3c0acc81603b01dc0df689683577b9

leeds_sports_pose

Leeds Sports Pose

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

[pdf]

[s2]

4b1d23d17476fcf78f4cbadf69fb130b1aa627c0

leeds_sports_pose_extended

Leeds Sports Pose Extended

Learning Effective Human Pose Estimation from Inaccurate Annotation

Learning effective human pose estimation from inaccurate annotation

[pdf]

[s2]

4e4746094bf60ee83e40d8597a6191e463b57f76

lfw

LFW

Labeled Faces in the Wild: A Survey

Labeled Faces in the Wild : A Survey

[pdf]

[s2]

7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22

lfw

LFW

Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

lfw

LFW

Labeled Faces in the Wild: Updates and New Reporting Procedures

Labeled Faces in the Wild : Updates and New Reporting Procedures

[pdf]

[s2]

University of Massachusetts

2d3482dcff69c7417c7b933f22de606a0e8e42d4

lfw_a

LFW-a

Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics

[pdf]

[s2]

133f01aec1534604d184d56de866a4bd531dac87

lfw_p

LFWP

Localizing Parts of Faces Using a Consensus of Exemplars

[pdf]

[s2]

Columbia University

140438a77a771a8fb656b39a78ff488066eb6b50

m2vts

The M2VTS Multimodal Face Database (Release 1.00)

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

[pdf]

[s2]

2485c98aa44131d1a2f7d1355b1e372f2bb148ad

m2vtsdb_extended

xm2vtsdb

XM2VTSDB: The Extended M2VTS Database

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

mafl

MAFL

Facial Landmark Detection by Deep Multi-task Learning

[pdf]

[s2]

Chinese University of Hong Kong

8a3c5507237957d013a0fe0f082cab7f757af6ee

mafl

MAFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

malf

MALF

Fine-grained Evaluation on Face Detection in the Wild.

Fine-grained evaluation on face detection in the wild

[pdf]

[s2]

Chinese Academy of Sciences

45e616093a92e5f1e61a7c6037d5f637aa8964af

mapillary

Mapillary

The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes

[pdf]

[s2]

79828e6e9f137a583082b8b5a9dfce0c301989b8

market_1501

Market 1501

Scalable Person Re-identification: A Benchmark

[pdf]

[s2]

4308bd8c28e37e2ed9a3fcfe74d5436cce34b410

market1203

Market 1203

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

mars

MARS

MARS: A Video Benchmark for Large-Scale Person Re-identification

MARS: A Video Benchmark for Large-Scale Person Re-Identification

[pdf]

[s2]

c0387e788a52f10bf35d4d50659cfa515d89fbec

mcgill

McGill Real World

Hierarchical Temporal Graphical Model for Head Pose Estimation and Subsequent Attribute Classification in Real-World Videos

Robust semi-automatic head pose labeling for real-world face video sequences

[pdf]

[s2]

McGill University

c570d1247e337f91e555c3be0e8c8a5aba539d9f

mcgill

McGill Real World

Robust Semi-automatic Head Pose Labeling for Real-World Face Video Sequences

Robust semi-automatic head pose labeling for real-world face video sequences

[pdf]

[s2]

McGill University

c570d1247e337f91e555c3be0e8c8a5aba539d9f

megaage

MegaAge

Quantifying Facial Age by Posterior of Age Comparisons

[pdf]

[s2]

Chinese University of Hong Kong

d80a3d1f3a438e02a6685e66ee908446766fefa9

megaface

MegaFace

The MegaFace Benchmark: 1 Million Faces for Recognition at Scale

[pdf]

[s2]

University of Washington

96e0cfcd81cdeb8282e29ef9ec9962b125f379b0

megaface

MegaFace

Level Playing Field for Million Scale Face Recognition

[pdf]

[s2]

28d4e027c7e90b51b7d8908fce68128d1964668a

mifs

MIFS

Spoofing Faces Using Makeup: An Investigative Study

Spoofing faces using makeup: An investigative study

[pdf]

[s2]

INRIA Méditerranée

23e824d1dfc33f3780dd18076284f07bd99f1c43

mit_cbcl

MIT CBCL

Component-based Face Recognition with 3D Morphable Models

Component-Based Face Recognition with 3D Morphable Models

[pdf]

[s2]

079a0a3bf5200994e1f972b1b9197bf2f90e87d4

miw

MIW

Automatic Facial Makeup Detection with Application in Face Recognition

Automatic facial makeup detection with application in face recognition

[pdf]

[s2]

West Virginia University

fcc6fe6007c322641796cb8792718641856a22a7

mmi_facial_expression

MMI Facial Expression Dataset

WEB-BASED DATABASE FOR FACIAL EXPRESSION ANALYSIS

Web-based database for facial expression analysis

[pdf]

[s2]

2a75f34663a60ab1b04a0049ed1d14335129e908

moments_in_time

Moments in Time

Moments in Time Dataset: one million videos for event understanding

[pdf]

[s2]

a5a44a32a91474f00a3cda671a802e87c899fbb4

morph

MORPH Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

morph_nc

MORPH Non-Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

mot

MOT

Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mot

MOT

Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mot

MOT

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mpi_large

Large MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

mpi_small

Small MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

mpii_gaze

MPIIGaze

Appearance-based Gaze Estimation in the Wild

Appearance-based gaze estimation in the wild

[pdf]

[s2]

Max Planck Institute for Informatics

0df0d1adea39a5bef318b74faa37de7f3e00b452

mpii_human_pose

MPII Human Pose

2D Human Pose Estimation: New Benchmark and State of the Art Analysis

[pdf]

[s2]

3325860c0c82a93b2eac654f5324dd6a776f609e

mr2

MR2

The MR2: A multi-racial mega-resolution database of facial stimuli

The MR2: A multi-racial, mega-resolution database of facial stimuli.

[pdf]

[s2]

578d4ad74818086bb64f182f72e2c8bd31e3d426

mrp_drone

MRP Drone

Investigating Open-World Person Re-identification Using a Drone

[pdf]

[s2]

ad01687649d95cd5b56d7399a9603c4b8e2217d7

msceleb

MsCeleb

MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition

[pdf]

[s2]

291265db88023e92bb8c8e6390438e5da148e8f5

msmt_17

MSMT17

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

[pdf]

[s2]

ec792ad2433b6579f2566c932ee414111e194537

mtfl

MTFL

Facial Landmark Detection by Deep Multi-task Learning

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

mtfl

MTFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

muct

MUCT

The MUCT Landmarked Face Database

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

mug_faces

MUG Faces

The MUG Facial Expression Database

The MUG facial expression database

[pdf]

[s2]

Aristotle University of Thessaloniki

f1af714b92372c8e606485a3982eab2f16772ad8

multi_pie

MULTIPIE

Multi-PIE

Scheduling heterogeneous multi-cores through performance impact estimation (PIE)

[pdf]

[s2]

109df0e8e5969ddf01e073143e83599228a1163f

names_and_faces_news

News Dataset

Names and Faces

Names and faces in the news

[pdf]

[s2]

2fda164863a06a92d3a910b96eef927269aeb730

nd_2006

ND-2006

Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition

[pdf]

[s2]

fd8168f1c50de85bac58a8d328df0a50248b16ae

nova_emotions

Novaemötions Dataset

Crowdsourcing facial expressions for affective-interaction

[pdf]

[s2]

c06b13d0ec3f5c43e2782cd22542588e233733c3

nova_emotions

Novaemötions Dataset

Competitive affective gamming: Winning with a smile

Competitive affective gaming: winning with a smile

[pdf]

[s2]

7f4040b482d16354d5938c1d1b926b544652bf5b

nudedetection

Nude Detection

A Bag-of-Features Approach based on Hue-SIFT Descriptor for Nude Detection

A bag-of-features approach based on Hue-SIFT descriptor for nude detection

[pdf]

[s2]

7ace44190729927e5cb0dd5d363fcae966fe13f7

orl

ORL

Parameterisation of a Stochastic Model for Human Face Identification

Parameterisation of a stochastic model for human face identification

[pdf]

[s2]

55206f0b5f57ce17358999145506cd01e570358c

penn_fudan

Penn Fudan

Object Detection Combining Recognition and Segmentation

[pdf]

[s2]

3394168ff0719b03ff65bcea35336a76b21fe5e4

peta

PETA

Pedestrian Attribute Recognition At Far Distance

[pdf]

[s2]

2a4bbee0b4cf52d5aadbbc662164f7efba89566c

pets

PETS 2017

PETS 2017: Dataset and Challenge

[pdf]

[s2]

22909dd19a0ec3b6065334cb5be5392cb24d839d

pilot_parliament

PPB

Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classication

Summary of Research on Informant Accuracy in Network Data, 11 and on the Reverse Small World Problem

[pdf]

[s2]

fb82681ac5d3487bd8e52dbb3d1fa220eeac855e

pipa

PIPA

Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues

Beyond frontal faces: Improving Person Recognition using multiple cues

[pdf]

[s2]

0a85bdff552615643dd74646ac881862a7c7072d

pku

PKU

Swiss-System Based Cascade Ranking for Gait-based Person Re-identification

Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification

[pdf]

[s2]

f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f

pku_reid

PKU-Reid

Orientation driven bag of appearances for person re-identification

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

pornodb

Pornography DB

Pooling in Image Representation: the Visual Codeword Point of View

Pooling in image representation: The visual codeword point of view

[pdf]

[s2]

b92a1ed9622b8268ae3ac9090e25789fc41cc9b8

precarious

Precarious

Expecting the Unexpected: Training Detectors for Unusual Pedestrians With Adversarial Imposters

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters

[pdf]

[s2]

9e5378e7b336c89735d3bb15cf67eff96f86d39a

prid

PRID

Person Re-Identification by Descriptive and Discriminative Classification

Person Re-identification by Descriptive and Discriminative Classification

[pdf]

[s2]

16c7c31a7553d99f1837fc6e88e77b5ccbb346b8

prw

PRW

Person Re-identification in the Wild

[pdf]

[s2]

University of Technology Sydney

0b84f07af44f964817675ad961def8a51406dd2e

psu

PSU

Vision-based Analysis of Small Groups in Pedestrian Crowds

Vision-Based Analysis of Small Groups in Pedestrian Crowds

[pdf]

[s2]

066000d44d6691d27202896691f08b27117918b9

pubfig

PubFig

Attribute and Simile Classifiers for Face Verification

Attribute and simile classifiers for face verification

[pdf]

[s2]

Columbia University

759a3b3821d9f0e08e0b0a62c8b693230afc3f8d

pubfig_83

pubfig83

Scaling Up Biologically-Inspired Computer Vision: A Case Study in Unconstrained Face Recognition on Facebook

Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook

[pdf]

[s2]

Harvard University

9c23859ec7313f2e756a3e85575735e0c52249f4

put_face

Put Face

The PUT face database

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

qmul_grid

GRID

Multi-Camera Activity Correlation Analysis

Multi-camera activity correlation analysis

[pdf]

[s2]

3b5b6d19d4733ab606c39c69a889f9e67967f151

qmul_grid

GRID

Time-delayed correlation analysis for multi-camera activity understanding

Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding

[pdf]

[s2]

2edb87494278ad11641b6cf7a3f8996de12b8e14

qmul_surv_face

QMUL-SurvFace

Surveillance Face Recognition Challenge

[pdf]

[s2]

c866a2afc871910e3282fd9498dce4ab20f6a332

rafd

RaFD

Presentation and validation of the Radboud Faces Database

[pdf]

[s2]

3765df816dc5a061bc261e190acc8bdd9d47bec0

raid

RAiD

Consistent Re-identification in a Camera Network

[pdf]

[s2]

09d78009687bec46e70efcf39d4612822e61cb8c

rap_pedestrian

RAP

A Richly Annotated Dataset for Pedestrian Attribute Recognition

[pdf]

[s2]

221c18238b829c12b911706947ab38fd017acef7

reseed

ReSEED

ReSEED: Social Event dEtection Dataset

ReSEED: social event dEtection dataset

[pdf]

[s2]

54983972aafc8e149259d913524581357b0f91c3

saivt

SAIVT SoftBio

A Database for Person Re-Identification in Multi-Camera Surveillance Networks

[pdf]

[s2]

22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b

sarc3d

Sarc3D

SARC3D: a new 3D body model for People Tracking and Re-identification

SARC3D: A New 3D Body Model for People Tracking and Re-identification

[pdf]

[s2]

e27ef52c641c2b5100a1b34fd0b819e84a31b4df

scface

SCface

SCface – surveillance cameras face database

Large Variability Surveillance Camera Face Database

[pdf]

[s2]

f3b84a03985de3890b400b68e2a92c0a00afd9d0

scut_fbp

SCUT-FBP

SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception

[pdf]

[s2]

South China University of Technology

bd26dabab576adb6af30484183c9c9c8379bf2e0

scut_head

SCUT HEAD

Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture

[pdf]

[s2]

d3200d49a19a4a4e4e9745ee39649b65d80c834b

sdu_vid

SDU-VID

A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification

[pdf]

[s2]

3b4ec8af470948a72a6ed37a9fd226719a874ebc

sdu_vid

SDU-VID

Local descriptors encoded by Fisher vectors for person re-identification

Local Descriptors Encoded by Fisher Vectors for Person Re-identification

[pdf]

[s2]

46a01565e6afe7c074affb752e7069ee3bf2e4ef

sdu_vid

SDU-VID

Person reidentification by video ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

sheffield

Sheffield Face

Face Recognition: From Theory to Applications

Face Description with Local Binary Patterns: Application to Face Recognition

[pdf]

[s2]

3607afdb204de9a5a9300ae98aa4635d9effcda2

social_relation

Social Relation

From Facial Expression Recognition to Interpersonal Relation Prediction

[pdf]

[s2]

22f656d0f8426c84a33a267977f511f127bfd7f3

social_relation

Social Relation

Learning Social Relation Traits from Face Images

[pdf]

[s2]

Chinese University of Hong Kong

2a171f8d14b6b8735001a11c217af9587d095848

soton

SOTON HiD

On a Large Sequence-Based Human Gait Database

On a large sequence-based human gait database

[pdf]

[s2]

4f93cd09785c6e77bf4bc5a788e079df524c8d21

sports_videos_in_the_wild

SVW

Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis

Sports Videos in the Wild (SVW): A video dataset for sports analysis

[pdf]

[s2]

Michigan State University

1a40092b493c6b8840257ab7f96051d1a4dbfeb2

stair_actions

STAIR Action

STAIR Actions: A Video Dataset of Everyday Home Actions

[pdf]

[s2]

d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9

stanford_drone

Stanford Drone

Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes

Social LSTM: Human Trajectory Prediction in Crowded Spaces

[pdf]

[s2]

570f37ed63142312e6ccdf00ecc376341ec72b9f

stickmen_buffy

Buffy Stickmen

Learning to Parse Images of Articulated Objects

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

stickmen_buffy

Buffy Stickmen

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

[pdf]

[s2]

4b1d23d17476fcf78f4cbadf69fb130b1aa627c0

stickmen_family

We Are Family Stickmen

We Are Family: Joint Pose Estimation of Multiple Persons

[pdf]

[s2]

0dc11a37cadda92886c56a6fb5191ded62099c28

stickmen_pascal

Stickmen PASCAL

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

stickmen_pascal

Stickmen PASCAL

Learning to Parse Images of Articulated Objects

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

sun_attributes

SUN

The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding

[pdf]

[s2]

66e6f08873325d37e0ec20a4769ce881e04e964e

sun_attributes

SUN

SUN Attribute Database: +Paper Title Sanity Check

Paper Title Sanity Check

key	name	our title	found title			address	s2 id
yfcc_100m	YFCC100M	YFCC100M: The New Data in Multimedia Research	YFCC100M: the new data in multimedia research	[pdf]	[s2]		010f0f4929e6a6644fb01f0e43820f91d0fad292
fiw_300	300-W	A semi-automatic methodology for facial landmark annotation	A Semi-automatic Methodology for Facial Landmark Annotation	[pdf]	[s2]	University of Twente	013909077ad843eb6df7a3e8e290cfd5575999d2
buhmap_db	BUHMAP-DB	Facial Feature Tracking and Expression Recognition for Sign Language	Facial feature tracking and expression recognition for sign language	[pdf]	[s2]		014b8df0180f33b9fea98f34ae611c6447d761d2
vqa	VQA	VQA: Visual Question Answering	VQA: Visual Question Answering	[pdf]	[s2]		01959ef569f74c286956024866c1d107099199f7
kitti	KITTI	Vision meets Robotics: The KITTI Dataset	Vision meets robotics: The KITTI dataset	[pdf]	[s2]		026e3363b7f76b51cc711886597a44d5f1fd1de2
ilids_mcts	i-LIDS	Imagery Library for Intelligent Detection Systems: The i-LIDS User Guide	Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems	[pdf]	[s2]		0297448f3ed948e136bb06ceff10eccb34e5bb77
ucf_selfie	UCF Selfie	How to Take a Good Selfie?	How to Take a Good Selfie?	[pdf]	[s2]		041d3eedf5e45ce5c5229f0181c5c576ed1fafd6
fiw_300	300-W	300 Faces in-the-Wild Challenge: The first facial landmark localization Challenge	300 Faces in-the-Wild Challenge: The First Facial Landmark Localization Challenge	[pdf]	[s2]	University of Twente	044d9a8c61383312cdafbcc44b9d00d650b21c70
chokepoint	ChokePoint	Patch-based Probabilistic Image Quality Assessment for Face Selection and Improved Video-based Face Recognition	Patch-based probabilistic image quality assessment for face selection and improved video-based face recognition	[pdf]	[s2]	University of Queensland	0486214fb58ee9a04edfe7d6a74c6d0f661a7668
hipsterwars	Hipsterwars	Hipster Wars: Discovering Elements of Fashion Styles	Hipster Wars: Discovering Elements of Fashion Styles	[pdf]	[s2]	Tohoku University	04c2cda00e5536f4b1508cbd80041e9552880e67
psu	PSU	Vision-based Analysis of Small Groups in Pedestrian Crowds	Vision-Based Analysis of Small Groups in Pedestrian Crowds	[pdf]	[s2]		066000d44d6691d27202896691f08b27117918b9
ifdb	IFDB	Iranian Face Database and Evaluation with a New Detection Algorithm	Iranian Face Database and Evaluation with a New Detection Algorithm	[pdf]	[s2]		066d71fcd997033dce4ca58df924397dfe0b5fd1
columbia_gaze	Columbia Gaze	Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction	Gaze locking: passive eye contact detection for human-object interaction	[pdf]	[s2]		06f02199690961ba52997cde1527e714d2b3bf8f
d3dfacs	D3DFACS	A FACS Valid 3D Dynamic Action Unit database with Applications to 3D Dynamic Morphable Facial Modelling	A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling	[pdf]	[s2]	Jacobs University	070de852bc6eb275d7ca3a9cdde8f6be8795d1a3
mit_cbcl	MIT CBCL	Component-based Face Recognition with 3D Morphable Models	Component-Based Face Recognition with 3D Morphable Models	[pdf]	[s2]		079a0a3bf5200994e1f972b1b9197bf2f90e87d4
uccs	UCCS	Large scale unconstrained open set face database	Large scale unconstrained open set face database	[pdf]	[s2]	University of Colorado at Colorado Springs	07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1
kin_face	UB KinFace	Understanding Kin Relationships in a Photo	Understanding Kin Relationships in a Photo	[pdf]	[s2]		08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7
raid	RAiD	Consistent Re-identification in a Camera Network	Consistent Re-identification in a Camera Network	[pdf]	[s2]		09d78009687bec46e70efcf39d4612822e61cb8c
pipa	PIPA	Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues	Beyond frontal faces: Improving Person Recognition using multiple cues	[pdf]	[s2]		0a85bdff552615643dd74646ac881862a7c7072d
kinectface	KinectFaceDB	KinectFaceDB: A Kinect Database for Face Recognition	KinectFaceDB: A Kinect Database for Face Recognition	[pdf]	[s2]		0b440695c822a8e35184fb2f60dcdaa8a6de84ae
prw	PRW	Person Re-identification in the Wild	Person Re-identification in the Wild	[pdf]	[s2]	University of Technology Sydney	0b84f07af44f964817675ad961def8a51406dd2e
feret	FERET	The FERET Verification Testing Protocol for Face Recognition Algorithms	The FERET Verification Testing Protocol for Face Recognition Algorithms	[pdf]	[s2]		0c4a139bb87c6743c7905b29a3cfec27a5130652
graz	Graz Pedestrian	Weak Hypotheses and Boosting for Generic Object Detection and Recognition	Weak Hypotheses and Boosting for Generic Object Detection and Recognition	[pdf]	[s2]		0c91808994a250d7be332400a534a9291ca3b60e
ijb_c	IJB-B	IARPA Janus Benchmark-B Face Dataset	IARPA Janus Benchmark-B Face Dataset	[pdf]	[s2]		0cb2dd5f178e3a297a0c33068961018659d0f443
casablanca	Casablanca	Context-aware {CNNs} for person head detection	Context-Aware CNNs for Person Head Detection	[pdf]	[s2]		0ceda9dae8b9f322df65ca2ef02caca9758aec6f
hollywood_headset	HollywoodHeads	Context-aware CNNs for person head detection	Context-Aware CNNs for Person Head Detection	[pdf]	[s2]		0ceda9dae8b9f322df65ca2ef02caca9758aec6f
lag	LAG	Large Age-Gap Face Verification by Feature Injection in Deep Networks	Large age-gap face verification by feature injection in deep networks	[pdf]	[s2]		0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e
face_scrub	FaceScrub	A data-driven approach to cleaning large face datasets	A data-driven approach to cleaning large face datasets	[pdf]	[s2]	University of Illinois, Urbana-Champaign	0d3bb75852098b25d90f31d2f48fd0cb4944702b
stickmen_family	We Are Family Stickmen	We Are Family: Joint Pose Estimation of Multiple Persons	We Are Family: Joint Pose Estimation of Multiple Persons	[pdf]	[s2]		0dc11a37cadda92886c56a6fb5191ded62099c28
mpii_gaze	MPIIGaze	Appearance-based Gaze Estimation in the Wild	Appearance-based gaze estimation in the wild	[pdf]	[s2]	Max Planck Institute for Informatics	0df0d1adea39a5bef318b74faa37de7f3e00b452
afw	AFW	Face detection, pose estimation and landmark localization in the wild	Face detection, pose estimation, and landmark localization in the wild	[pdf]	[s2]	University of California, Irvine	0e986f51fe45b00633de9fd0c94d082d2be51406
voc	VOC	The PASCAL Visual Object Classes (VOC) Challenge	The Pascal Visual Object Classes (VOC) Challenge	[pdf]	[s2]		0ee1916a0cb2dc7d3add086b5f1092c3d4beb38a
feret	FERET	The FERET Evaluation Methodology for Face-Recognition Algorithms	The FERET Evaluation Methodology for Face-Recognition Algorithms	[pdf]	[s2]		0f0fcf041559703998abf310e56f8a2f90ee6f21
imdb_wiki	IMDB	Deep expectation of real and apparent age from a single image without facial landmarks	Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks	[pdf]	[s2]		10195a163ab6348eef37213a46f60a3d87f289c5
inria_person	INRIA Pedestrian	Histograms of Oriented Gradients for Human Detection	Histograms of oriented gradients for human detection	[pdf]	[s2]		10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5
graz	Graz Pedestrian	Object Recognition Using Segmentation for Feature Detection	Object recognition using segmentation for feature detection	[pdf]	[s2]		12ad3b5bbbf407f8e54ea692c07633d1a867c566
lfw_a	LFW-a	Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics	Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics	[pdf]	[s2]		133f01aec1534604d184d56de866a4bd531dac87
hrt_transgender	HRT Transgender	Is the Eye Region More Reliable Than the Face? A Preliminary Study of Face-based Recognition on a Transgender Dataset	Is the eye region more reliable than the face? A preliminary study of face-based recognition on a transgender dataset	[pdf]	[s2]	University of North Carolina Wilmington	137aa2f891d474fce1e7a1d1e9b3aefe21e22b34
eth_andreas_ess	ETHZ Pedestrian	Depth and Appearance for Mobile Scene Analysis	Depth and Appearance for Mobile Scene Analysis	[pdf]	[s2]		13f06b08f371ba8b5d31c3e288b4deb61335b462
lfw_p	LFWP	Localizing Parts of Faces Using a Consensus of Exemplars	Localizing Parts of Faces Using a Consensus of Exemplars	[pdf]	[s2]	Columbia University	140438a77a771a8fb656b39a78ff488066eb6b50
ijb_c	IJB-A	Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A	Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A	[pdf]	[s2]		140c95e53c619eac594d70f6369f518adfea12ef
vgg_faces	VGG Face	Deep Face Recognition	Deep Face Recognition	[pdf]	[s2]		162ea969d1929ed180cc6de9f0bf116993ff6e06
prid	PRID	Person Re-Identification by Descriptive and Discriminative Classification	Person Re-identification by Descriptive and Discriminative Classification	[pdf]	[s2]		16c7c31a7553d99f1837fc6e88e77b5ccbb346b8
umb	UMB	UMB-DB: A Database of Partially Occluded 3D Faces	UMB-DB: A database of partially occluded 3D faces	[pdf]	[s2]		16e8b0a1e8451d5f697b94c0c2b32a00abee1d52
celeba_plus	CelebFaces+	Deep Learning Face Representation from Predicting 10,000 Classes	Deep Learning Face Representation from Predicting 10,000 Classes	[pdf]	[s2]	Shenzhen Institutes of Advanced Technology	177bc509dd0c7b8d388bb47403f28d6228c14b5c
geofaces	GeoFaces	GeoFaceExplorer: Exploring the Geo-Dependence of Facial Attributes	GeoFaceExplorer: exploring the geo-dependence of facial attributes	[pdf]	[s2]	University of Kentucky	17b46e2dad927836c689d6787ddb3387c6159ece
deep_fashion	DeepFashion	DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations	DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations	[pdf]	[s2]		18010284894ed0edcca74e5bf768ee2e15ef7841
pilot_parliament	PPB	Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification	Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification	[pdf]	[s2]		18858cc936947fc96b5c06bbe3c6c2faa5614540
frgc	FRGC	Overview of the Face Recognition Grand Challenge	Overview of the face recognition grand challenge	[pdf]	[s2]		18ae7c9a4bbc832b8b14bc4122070d7939f5e00e
yale_faces	YaleFaces	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	[pdf]	[s2]		18c72175ddbb7d5956d180b65a96005c100f6014
york_3d	UOY 3D Face Database	Three-Dimensional Face Recognition: An Eigensurface Approach	Three-dimensional face recognition: an eigensurface approach	[pdf]	[s2]		19d1b811df60f86cbd5e04a094b07f32fff7a32a
sports_videos_in_the_wild	SVW	Sports Videos in the Wild (SVW): A Video Dataset for Sports Analysis	Sports Videos in the Wild (SVW): A video dataset for sports analysis	[pdf]	[s2]	Michigan State University	1a40092b493c6b8840257ab7f96051d1a4dbfeb2
jpl_pose	JPL-Interaction dataset	First-Person Activity Recognition: What Are They Doing to Me?	First-Person Activity Recognition: What Are They Doing to Me?	[pdf]	[s2]		1aad2da473888cb7ebc1bfaa15bfa0f1502ce005
adience	Adience	Age and Gender Estimation of Unfiltered Faces	Age and Gender Estimation of Unfiltered Faces	[pdf]	[s2]		1be498d4bbc30c3bfd0029114c784bc2114d67c0
youtube_poses	YouTube Pose	Personalizing Human Video Pose Estimation	Personalizing Human Video Pose Estimation	[pdf]	[s2]		1c2802c2199b6d15ecefe7ba0c39bfe44363de38
caltech_pedestrians	Caltech Pedestrians	Pedestrian Detection: A Benchmark	Pedestrian detection: A benchmark	[pdf]	[s2]		1dc35905a1deff8bc74688f2d7e2f48fd2273275
immediacy	Immediacy	Multi-task Recurrent Neural Network for Immediacy Prediction	Multi-task Recurrent Neural Network for Immediacy Prediction	[pdf]	[s2]		1e3df3ca8feab0b36fd293fe689f93bb2aaac591
cafe	CAFE	The Child Affective Facial Expression (CAFE) Set: Validity and reliability from untrained adults	The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults	[pdf]	[s2]		20388099cc415c772926e47bcbbe554e133343d1
bbc_pose	BBC Pose	Automatic and Efficient Human Pose Estimation for Sign Language Videos	Automatic and Efficient Human Pose Estimation for Sign Language Videos	[pdf]	[s2]		213a579af9e4f57f071b884aa872651372b661fd
3d_rma	3D-RMA	Automatic 3D Face Authentication	Automatic 3D face authentication	[pdf]	[s2]		2160788824c4c29ffe213b2cbeb3f52972d73f37
large_scale_person_search	Large Scale Person Search	End-to-End Deep Learning for Person Search	End-to-End Deep Learning for Person Search	[pdf]	[s2]		2161f6b7ee3c0acc81603b01dc0df689683577b9
images_of_groups	Images of Groups	Understanding Groups of Images of People	Understanding images of groups of people	[pdf]	[s2]		21d9d0deed16f0ad62a4865e9acf0686f4f15492
rap_pedestrian	RAP	A Richly Annotated Dataset for Pedestrian Attribute Recognition	A Richly Annotated Dataset for Pedestrian Attribute Recognition	[pdf]	[s2]		221c18238b829c12b911706947ab38fd017acef7
mot	MOT	Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics	Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics	[pdf]	[s2]		2258e01865367018ed6f4262c880df85b94959f8
saivt	SAIVT SoftBio	A Database for Person Re-Identification in Multi-Camera Surveillance Networks	A Database for Person Re-Identification in Multi-Camera Surveillance Networks	[pdf]	[s2]		22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b
pets	PETS 2017	PETS 2017: Dataset and Challenge	PETS 2017: Dataset and Challenge	[pdf]	[s2]		22909dd19a0ec3b6065334cb5be5392cb24d839d
gallagher	Gallagher	Clothing Cosegmentation for Recognizing People	Clothing cosegmentation for recognizing people	[pdf]	[s2]		22ad2c8c0f4d6aa4328b38d894b814ec22579761
expw	ExpW	From Facial Expression Recognition to Interpersonal Relation Prediction	From Facial Expression Recognition to Interpersonal Relation Prediction	[pdf]	[s2]		22f656d0f8426c84a33a267977f511f127bfd7f3
mifs	MIFS	Spoofing Faces Using Makeup: An Investigative Study	Spoofing faces using makeup: An investigative study	[pdf]	[s2]	INRIA Méditerranée	23e824d1dfc33f3780dd18076284f07bd99f1c43
cohn_kanade	CK	Comprehensive Database for Facial Expression Analysis	Comprehensive Database for Facial Expression Analysis	[pdf]	[s2]	Carnegie Mellon University	23fc83c8cfff14a16df7ca497661264fc54ed746
cas_peal	CAS-PEAL	The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations	The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations	[pdf]	[s2]		2485c98aa44131d1a2f7d1355b1e372f2bb148ad
faceplace	Face Place	Recognizing disguised faces	Recognizing disguised faces	[pdf]	[s2]		25474c21613607f6bb7687a281d5f9d4ffa1f9f3
afew_va	AFEW-VA	AFEW-VA database for valence and arousal estimation in-the-wild	AFEW-VA database for valence and arousal estimation in-the-wild	[pdf]	[s2]		2624d84503bc2f8e190e061c5480b6aa4d89277a
cofw	COFW	Robust face landmark estimation under occlusion	Robust Face Landmark Estimation under Occlusion	[pdf]	[s2]		2724ba85ec4a66de18da33925e537f3902f21249
duke_mtmc	Duke MTMC	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	[pdf]	[s2]		27a2fad58dd8727e280f97036e0d2bc55ef5424c
mot	MOT	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	[pdf]	[s2]		27a2fad58dd8727e280f97036e0d2bc55ef5424c
h3d	H3D	Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations	Poselets: Body part detectors trained using 3D human pose annotations	[pdf]	[s2]		2830fb5282de23d7784b4b4bc37065d27839a412
megaface	MegaFace	Level Playing Field for Million Scale Face Recognition	Level Playing Field for Million Scale Face Recognition	[pdf]	[s2]		28d4e027c7e90b51b7d8908fce68128d1964668a
msceleb	MsCeleb	MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition	MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition	[pdf]	[s2]		291265db88023e92bb8c8e6390438e5da148e8f5
ferplus	FER+	Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution	Training deep networks for facial expression recognition with crowd-sourced label distribution	[pdf]	[s2]		298cbc3dfbbb3a20af4eed97906650a4ea1c29e0
scface	SCface	SCface – surveillance cameras face database	SCface – surveillance cameras face database	[pdf]	[s2]		29a705a5fa76641e0d8963f1fdd67ee4c0d92d3d
social_relation	Social Relation	Learning Social Relation Traits from Face Images	Learning Social Relation Traits from Face Images	[pdf]	[s2]	Chinese University of Hong Kong	2a171f8d14b6b8735001a11c217af9587d095848
peta	PETA	Pedestrian Attribute Recognition At Far Distance	Pedestrian Attribute Recognition At Far Distance	[pdf]	[s2]		2a4bbee0b4cf52d5aadbbc662164f7efba89566c
mmi_facial_expression	MMI Facial Expression Dataset	WEB-BASED DATABASE FOR FACIAL EXPRESSION ANALYSIS	Web-based database for facial expression analysis	[pdf]	[s2]		2a75f34663a60ab1b04a0049ed1d14335129e908
bosphorus	The Bosphorus	Bosphorus Database for 3D Face Analysis	Bosphorus Database for 3D Face Analysis	[pdf]	[s2]		2acf7e58f0a526b957be2099c10aab693f795973
yale_faces	YaleFaces	Acquiring Linear Subspaces for Face Recognition under Variable Lighting	Acquiring linear subspaces for face recognition under variable lighting	[pdf]	[s2]		2ad0ee93d029e790ebb50574f403a09854b65b7e
frav3d	FRAV3D	MULTIMODAL 2D, 2.5D & 3D FACE VERIFICATION	Multimodal 2D, 2.5D & 3D Face Verification	[pdf]	[s2]		2b926b3586399d028b46315d7d9fb9d879e4f79c
clothing_co_parsing	CCP	Clothing Co-Parsing by Joint Image Segmentation and Labeling	Clothing Co-parsing by Joint Image Segmentation and Labeling	[pdf]	[s2]		2bf8541199728262f78d4dced6fb91479b39b738
texas_3dfrd	Texas 3DFRD	Anthropometric 3D Face Recognition	Anthropometric 3D Face Recognition	[pdf]	[s2]		2ce2560cf59db59ce313bbeb004e8ce55c5ce928
lfw	LFW	Labeled Faces in the Wild: Updates and New Reporting Procedures	Labeled Faces in the Wild : Updates and New Reporting Procedures	[pdf]	[s2]	University of Massachusetts	2d3482dcff69c7417c7b933f22de606a0e8e42d4
a_pascal_yahoo	aPascal	Describing Objects by their Attributes	Describing objects by their attributes	[pdf]	[s2]		2e384f057211426ac5922f1b33d2aa8df5d51f57
3dpes	3DPeS	3DPes: 3D People Dataset for Surveillance and Forensics	3DPeS: 3D people dataset for surveillance and forensics	[pdf]	[s2]		2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e
kin_face	UB KinFace	Genealogical Face Recognition based on UB KinFace Database	Genealogical face recognition based on UB KinFace database	[pdf]	[s2]	SUNY Buffalo	2eb84aaba316b095d4bb51da1a3e4365bbf9ab1d
qmul_grid	GRID	Time-delayed correlation analysis for multi-camera activity understanding	Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding	[pdf]	[s2]		2edb87494278ad11641b6cf7a3f8996de12b8e14
graz	Graz Pedestrian	Generic Object Recognition with Boosting	Generic object recognition with boosting	[pdf]	[s2]		2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9
hrt_transgender	HRT Transgender	Investigating the Periocular-Based Face Recognition Across Gender Transformation	Investigating the Periocular-Based Face Recognition Across Gender Transformation	[pdf]	[s2]	University of North Carolina at Wilmington	2f43b614607163abf41dfe5d17ef6749a1b61304
names_and_faces_news	News Dataset	Names and Faces	Names and faces in the news	[pdf]	[s2]		2fda164863a06a92d3a910b96eef927269aeb730
umd_faces	UMD	UMDFaces: An Annotated Face Dataset for Training Deep Networks	UMDFaces: An annotated face dataset for training deep networks	[pdf]	[s2]		31b05f65405534a696a847dd19c621b7b8588263
tiny_images	Tiny Images	80 million tiny images: a large dataset for non-parametric object and scene recognition	80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition	[pdf]	[s2]		31b58ced31f22eab10bd3ee2d9174e7c14c27c01
feret	FERET	FERET ( Face Recognition Technology ) Recognition Algorithm Development and Test Results	FERET ( Face Recognition Technology ) Recognition Algorithm Development and Test Results	[pdf]	[s2]		31de9b3dd6106ce6eec9a35991b2b9083395fd0b
ucf_crowd	UCF-CC-50	Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images	Multi-source Multi-scale Counting in Extremely Dense Crowd Images	[pdf]	[s2]		32c801cb7fbeb742edfd94cccfca4934baec71da
cityscapes	Cityscapes	The Cityscapes Dataset for Semantic Urban Scene Understanding	The Cityscapes Dataset for Semantic Urban Scene Understanding	[pdf]	[s2]		32cde90437ab5a70cf003ea36f66f2de0e24b3ab
tud_campus	TUD-Campus	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]		3316521a5527c7700af8ae6aef32a79a8b83672c
tud_crossing	TUD-Crossing	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]		3316521a5527c7700af8ae6aef32a79a8b83672c
tud_pedestrian	TUD-Pedestrian	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]		3316521a5527c7700af8ae6aef32a79a8b83672c
mpii_human_pose	MPII Human Pose	2D Human Pose Estimation: New Benchmark and State of the Art Analysis	2D Human Pose Estimation: New Benchmark and State of the Art Analysis	[pdf]	[s2]		3325860c0c82a93b2eac654f5324dd6a776f609e
penn_fudan	Penn Fudan	Object Detection Combining Recognition and Segmentation	Object Detection Combining Recognition and Segmentation	[pdf]	[s2]		3394168ff0719b03ff65bcea35336a76b21fe5e4
wider	WIDER	Recognize Complex Events from Static Images by Fusing Deep Channels	Recognize complex events from static images by fusing deep channels	[pdf]	[s2]	Shenzhen Institutes of Advanced Technology	356b431d4f7a2a0a38cf971c84568207dcdbf189
coco_qa	COCO QA	Exploring Models and Data for Image Question Answering	Exploring Models and Data for Image Question Answering	[pdf]	[s2]		35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62
lfw	LFW	Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments	Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments	[pdf]	[s2]		370b5757a5379b15e30d619e4d3fb9e8e13f3256
rafd	RaFD	Presentation and validation of the Radboud Faces Database	Presentation and validation of the Radboud Faces Database	[pdf]	[s2]		3765df816dc5a061bc261e190acc8bdd9d47bec0
ufdd	UFDD	Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results	Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results	[pdf]	[s2]	Johns Hopkins University	377f2b65e6a9300448bdccf678cde59449ecd337
vmu	VMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]		37d6f0eb074d207b53885bd2eb78ccc8a04be597
youtube_makeup	YMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]		37d6f0eb074d207b53885bd2eb78ccc8a04be597
cuhk02	CUHK02	Locally Aligned Feature Transforms across Views	Locally Aligned Feature Transforms across Views	[pdf]	[s2]		38b55d95189c5e69cf4ab45098a48fba407609b4
sdu_vid	SDU-VID	A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification	A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification	[pdf]	[s2]		3b4ec8af470948a72a6ed37a9fd226719a874ebc
qmul_grid	GRID	Multi-Camera Activity Correlation Analysis	Multi-camera activity correlation analysis	[pdf]	[s2]		3b5b6d19d4733ab606c39c69a889f9e67967f151
tvhi	TVHI	High Five: Recognising human interactions in TV shows	High Five: Recognising human interactions in TV shows	[pdf]	[s2]		3cd40bfa1ff193a96bde0207e5140a399476466c
georgia_tech_face_database	Georgia Tech Face	Maximum likelihood training of the embedded HMM for face detection and recognition	MAXIMUM LIKELIHOOD TRAINING OF THE EMBEDDED HMM FOR FACE DETECTION AND RECOGNITION Ara V. Ne an and Monson H. Hayes III Center for Signal and Image Processing School of Electrical and Computer Engineering	[pdf]	[s2]		3dc3f0b64ef80f573e3a5f96e456e52ee980b877
bio_id	BioID Face	Robust Face Detection Using the Hausdorff Distance	Robust Face Detection Using the Hausdorff Distance	[pdf]	[s2]		4053e3423fb70ad9140ca89351df49675197196a
distance_nighttime	Long Distance Heterogeneous Face	Nighttime Face Recognition at Long Distance: Cross-distance and Cross-spectral Matching	Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching	[pdf]	[s2]		4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06
market_1501	Market 1501	Scalable Person Re-identification: A Benchmark	Scalable Person Re-identification: A Benchmark	[pdf]	[s2]		4308bd8c28e37e2ed9a3fcfe74d5436cce34b410
tud_multiview	TUD-Multiview	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]		436f798d1a4e54e5947c1e7d7375c31b2bdb4064
tud_stadtmitte	TUD-Stadtmitte	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]		436f798d1a4e54e5947c1e7d7375c31b2bdb4064
cuhk01	CUHK01	Human Reidentification with Transferred Metric Learning	Human Reidentification with Transferred Metric Learning	[pdf]	[s2]		44484d2866f222bbb9b6b0870890f9eea1ffb2d0
wider_attribute	WIDER Attribute	Human Attribute Recognition by Deep Hierarchical Contexts	Human Attribute Recognition by Deep Hierarchical Contexts	[pdf]	[s2]	Chinese University of Hong Kong	44d23df380af207f5ac5b41459c722c87283e1eb
vadana	VADANA	VADANA: A dense dataset for facial image analysis	VADANA: A dense dataset for facial image analysis	[pdf]	[s2]		4563b46d42079242f06567b3f2e2f7a80cb3befe
jaffe	JAFFE	Coding Facial Expressions with Gabor Wavelets	Coding Facial Expressions with Gabor Wavelets	[pdf]	[s2]	Kyushu University	45c31cde87258414f33412b3b12fc5bec7cb3ba9
malf	MALF	Fine-grained Evaluation on Face Detection in the Wild.	Fine-grained evaluation on face detection in the wild	[pdf]	[s2]	Chinese Academy of Sciences	45e616093a92e5f1e61a7c6037d5f637aa8964af
sdu_vid	SDU-VID	Local descriptors encoded by Fisher vectors for person re-identification	Local Descriptors Encoded by Fisher Vectors for Person Re-identification	[pdf]	[s2]		46a01565e6afe7c074affb752e7069ee3bf2e4ef
fia	CMU FiA	The CMU Face In Action (FIA) Database	The CMU Face In Action (FIA) Database	[pdf]	[s2]		47662d1a368daf70ba70ef2d59eb6209f98b675d
kin_face	UB KinFace	Kinship Verification through Transfer Learning	Kinship Verification through Transfer Learning	[pdf]	[s2]		4793f11fbca4a7dba898b9fff68f70d868e2497c
am_fed	AM-FED	Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”	Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"	[pdf]	[s2]		47aeb3b82f54b5ae8142b4bdda7b614433e69b9a
apis	APiS1.0	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	[pdf]	[s2]		488e475eeb3bb39a145f23ede197cd3620f1d98a
svs	SVS	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	[pdf]	[s2]		488e475eeb3bb39a145f23ede197cd3620f1d98a
coco_action	COCO-a	Describing Common Human Visual Actions in Images	Describing Common Human Visual Actions in Images	[pdf]	[s2]		4946ba10a4d5a7d0a38372f23e6622bd347ae273
leeds_sports_pose	Leeds Sports Pose	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	[pdf]	[s2]		4b1d23d17476fcf78f4cbadf69fb130b1aa627c0
stickmen_buffy	Buffy Stickmen	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	[pdf]	[s2]		4b1d23d17476fcf78f4cbadf69fb130b1aa627c0
czech_news_agency	UFI	Unconstrained Facial Images: Database for Face Recognition under Real-world Conditions	Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions	[pdf]	[s2]		4b4106614c1d553365bad75d7866bff0de6056ed
face_tracer	FaceTracer	FaceTracer: A Search Engine for Large Collections of Images with Faces	FaceTracer: A Search Engine for Large Collections of Images with Faces	[pdf]	[s2]	Columbia University	4c170a0dcc8de75587dae21ca508dab2f9343974
cmu_pie	CMU PIE	The CMU Pose, Illumination, and Expression Database	The CMU Pose, Illumination, and Expression (PIE) Database	[pdf]	[s2]		4d423acc78273b75134e2afd1777ba6d3a398973
multi_pie	MULTIPIE	Multi-PIE	The CMU Pose, Illumination, and Expression (PIE) Database	[pdf]	[s2]		4d423acc78273b75134e2afd1777ba6d3a398973
3dddb_unconstrained	3D Dynamic	A 3D Dynamic Database for Unconstrained Face Recognition	A 3 D Dynamic Database for Unconstrained Face Recognition	[pdf]	[s2]		4d4bb462c9f1d4e4ab1e4aa6a75cc0bc71b38461
texas_3dfrd	Texas 3DFRD	Texas 3D Face Recognition Database	Texas 3D Face Recognition Database	[pdf]	[s2]		4d58f886f5150b2d5e48fd1b5a49e09799bf895d
cohn_kanade_plus	CK+	The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression	The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression	[pdf]	[s2]		4d9a02d080636e9666c4d1cc438b9893391ec6c7
cfd	CFD	The Chicago face database: A free stimulus set of faces and norming data	The Chicago face database: A free stimulus set of faces and norming data.	[pdf]	[s2]		4df3143922bcdf7db78eb91e6b5359d6ada004d2
leeds_sports_pose_extended	Leeds Sports Pose Extended	Learning Effective Human Pose Estimation from Inaccurate Annotation	Learning effective human pose estimation from inaccurate annotation	[pdf]	[s2]		4e4746094bf60ee83e40d8597a6191e463b57f76
dartmouth_children	Dartmouth Children	The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set	The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set	[pdf]	[s2]		4e6ee936eb50dd032f7138702fa39b7c18ee8907
soton	SOTON HiD	On a Large Sequence-Based Human Gait Database	On a large sequence-based human gait database	[pdf]	[s2]		4f93cd09785c6e77bf4bc5a788e079df524c8d21
deep_fashion	DeepFashion	Fashion Landmark Detection in the Wild	Fashion Landmark Detection in the Wild	[pdf]	[s2]	Chinese University of Hong Kong	4fefd1bc8dc4e0ab37ee3324ddfa43ad9d6a04a7
violent_flows	Violent Flows	Violent Flows: Real-Time Detection of Violent Crowd Behavior	Violent flows: Real-time detection of violent crowd behavior	[pdf]	[s2]		5194cbd51f9769ab25260446b4fa17204752e799
imsitu	imSitu	Situation Recognition: Visual Semantic Role Labeling for Image Understanding	Situation Recognition: Visual Semantic Role Labeling for Image Understanding	[pdf]	[s2]	University of Washington	51eba481dac6b229a7490f650dff7b17ce05df73
wider_face	WIDER FACE	WIDER FACE: A Face Detection Benchmark	WIDER FACE: A Face Detection Benchmark	[pdf]	[s2]	Chinese University of Hong Kong	52d7eb0fbc3522434c13cc247549f74bb9609c5d
bp4d_plus	BP4D+	Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis	Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis	[pdf]	[s2]		53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4
reseed	ReSEED	ReSEED: Social Event dEtection Dataset	ReSEED: social event dEtection dataset	[pdf]	[s2]		54983972aafc8e149259d913524581357b0f91c3
orl	ORL	Parameterisation of a Stochastic Model for Human Face Identification	Parameterisation of a stochastic model for human face identification	[pdf]	[s2]		55206f0b5f57ce17358999145506cd01e570358c
ifad	IFAD	Indian Face Age Database: A Database for Face Recognition with Age Variation	Indian Face Age Database : A Database for Face Recognition with Age Variation	[pdf]	[s2]		55c40cbcf49a0225e72d911d762c27bb1c2d14aa
youtube_faces	YouTubeFaces	Face Recognition in Unconstrained Videos with Matched Background Similarity	Face recognition in unconstrained videos with matched background similarity	[pdf]	[s2]	Open University of Israel	560e0e58d0059259ddf86fcec1fa7975dee6a868
data_61	Data61 Pedestrian	A Multi-Modal Graphical Model for Scene Analysis	A Multi-modal Graphical Model for Scene Analysis	[pdf]	[s2]		563c940054e4b456661762c1ab858e6f730c3159
cmdp	CMDP	Distance Estimation of an Unknown Person from a Portrait	Distance Estimation of an Unknown Person from a Portrait	[pdf]	[s2]	California Institute of Technology	56ae6d94fc6097ec4ca861f0daa87941d1c10b70
unbc_shoulder_pain	UNBC-McMaster Pain	PAINFUL DATA: The UNBC-McMaster Shoulder Pain Expression Archive Database	Painful data: The UNBC-McMaster shoulder pain expression archive database	[pdf]	[s2]		56ffa7d906b08d02d6d5a12c7377a57e24ef3391
stanford_drone	Stanford Drone	Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes	Social LSTM: Human Trajectory Prediction in Crowded Spaces	[pdf]	[s2]		570f37ed63142312e6ccdf00ecc376341ec72b9f
ijb_c	IJB-C	IARPA Janus Benchmark C	IARPA Janus Benchmark - C: Face Dataset and Protocol	[pdf]	[s2]		57178b36c21fd7f4529ac6748614bb3374714e91
50_people_one_question	50 People One Question	Merging Pose Estimates Across Space and Time	Merging Pose Estimates Across Space and Time	[pdf]	[s2]		5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725
mr2	MR2	The MR2: A multi-racial mega-resolution database of facial stimuli	The MR2: A multi-racial, mega-resolution database of facial stimuli.	[pdf]	[s2]		578d4ad74818086bb64f182f72e2c8bd31e3d426
cvc_01_barcelona	CVC-01	Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection	Adaptive Image Sampling and Windows Classification for On – board Pedestrian Detection	[pdf]	[s2]		57fe081950f21ca03b5b375ae3e84b399c015861
mot	MOT	Learning to associate: HybridBoosted multi-target tracker for crowded scene	Learning to associate: HybridBoosted multi-target tracker for crowded scene	[pdf]	[s2]		5981e6479c3fd4e31644db35d236bfb84ae46514
disfa	DISFA	DISFA: A Spontaneous Facial Action Intensity Database	DISFA: A Spontaneous Facial Action Intensity Database	[pdf]	[s2]		5a5f0287484f0d480fed1ce585dbf729586f0edc
wlfdb	WLFDB	WLFDB: Weakly Labeled Face Databases	WLFDB: Weakly Labeled Face Databases	[pdf]	[s2]		5ad4e9f947c1653c247d418f05dad758a3f9277b
coco	COCO	Microsoft COCO: Common Objects in Context	Microsoft COCO: Common Objects in Context	[pdf]	[s2]		5e0f8c355a37a5a89351c02f174e7a5ddcb98683
cityscapes	Cityscapes	The Cityscapes Dataset	The Cityscapes Dataset	[pdf]	[s2]		5ffd74d2873b7cba2cbc5fd295cc7fbdedca22a2
viper	VIPeR	Evaluating Appearance Models for Recognition, Reacquisition, and Tracking	Evaluating Appearance Models for Recognition , Reacquisition , and Tracking	[pdf]	[s2]		6273b3491e94ea4dd1ce42b791d77bdc96ee73a8
caltech_10k_web_faces	Caltech 10K Web Faces	Pruning Training Sets for Learning of Object Categories	Pruning training sets for learning of object categories	[pdf]	[s2]		636b8ffc09b1b23ff714ac8350bb35635e49fa3c
bfm	BFM	A 3D Face Model for Pose and Illumination Invariant Face Recognition	A 3D Face Model for Pose and Illumination Invariant Face Recognition	[pdf]	[s2]		639937b3a1b8bded3f7e9a40e85bd3770016cf3c
alert_airport	ALERT Airport	A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets	A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.	[pdf]	[s2]		6403117f9c005ae81f1e8e6d1302f4a045e3d99d
celeba	CelebA	Deep Learning Face Attributes in the Wild	Deep Learning Face Attributes in the Wild	[pdf]	[s2]	Chinese University of Hong Kong	6424b69f3ff4d35249c0bb7ef912fbc2c86f4ff4
complex_activities	Ongoing Complex Activities	Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space	Recognition of ongoing complex activities by sequence prediction over a hierarchical label space	[pdf]	[s2]		65355cbb581a219bd7461d48b3afd115263ea760
afad	AFAD	Ordinal Regression with a Multiple Output CNN for Age Estimation	Ordinal Regression with Multiple Output CNN for Age Estimation	[pdf]	[s2]		6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c
sun_attributes	SUN	The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding	The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding	[pdf]	[s2]		66e6f08873325d37e0ec20a4769ce881e04e964e
face_tracer	FaceTracer	Face Swapping: Automatically Replacing Faces in Photographs	Face swapping: automatically replacing faces in photographs	[pdf]	[s2]	Columbia University	670637d0303a863c1548d5b19f705860a23e285c
tud_brussels	TUD-Brussels	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]		6ad5a38df8dd4cdddd74f31996ce096d41219f72
tud_motionpairs	TUD-Motionparis	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]		6ad5a38df8dd4cdddd74f31996ce096d41219f72
cuhk03	CUHK03	DeepReID: Deep Filter Pairing Neural Network for Person Re-identification	DeepReID: Deep Filter Pairing Neural Network for Person Re-identification	[pdf]	[s2]		6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3
ar_facedb	AR Face	The AR Face Database	The AR face database	[pdf]	[s2]		6d96f946aaabc734af7fe3fc4454cf8547fcd5ed
agedb	AgeDB	AgeDB: the first manually collected, in-the-wild age database	AgeDB: The First Manually Collected, In-the-Wild Age Database	[pdf]	[s2]		6dcf418c778f528b5792104760f1fbfe90c6dd6a
stickmen_buffy	Buffy Stickmen	Learning to Parse Images of Articulated Objects	Learning to parse images of articulated bodies	[pdf]	[s2]		6dd0597f8513dc100cd0bc1b493768cde45098a9
stickmen_pascal	Stickmen PASCAL	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Learning to parse images of articulated bodies	[pdf]	[s2]		6dd0597f8513dc100cd0bc1b493768cde45098a9
stickmen_pascal	Stickmen PASCAL	Learning to Parse Images of Articulated Objects	Learning to parse images of articulated bodies	[pdf]	[s2]		6dd0597f8513dc100cd0bc1b493768cde45098a9
ward	WARD	Re-identify people in wide area camera network	Re-identify people in wide area camera network	[pdf]	[s2]		6f3c76b7c0bd8e1d122c6ea808a271fd4749c951
umd_faces	UMD	The Do's and Don'ts for CNN-based Face Verification	The Do’s and Don’ts for CNN-Based Face Verification	[pdf]	[s2]		71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6
affectnet	AffectNet	AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild	AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild	[pdf]	[s2]		758d7e1be64cc668c59ef33ba8882c8597406e53
pubfig	PubFig	Attribute and Simile Classifiers for Face Verification	Attribute and simile classifiers for face verification	[pdf]	[s2]	Columbia University	759a3b3821d9f0e08e0b0a62c8b693230afc3f8d
fddb	FDDB	FDDB: A Benchmark for Face Detection in Unconstrained Settings	A Benchmark for Face Detection in Unconstrained Settings	[pdf]	[s2]	University of Massachusetts	75da1df4ed319926c544eefe17ec8d720feef8c0
urban_tribes	Urban Tribes	From Bikers to Surfers: Visual Recognition of Urban Tribes	From Bikers to Surfers: Visual Recognition of Urban Tribes	[pdf]	[s2]	Columbia University	774cbb45968607a027ae4729077734db000a1ec5
wildtrack	WildTrack	WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	[pdf]	[s2]		77c81c13a110a341c140995bedb98101b9e84f7f
berkeley_pose	BPAD	Describing People: A Poselet-Based Approach to Attribute Classification	Describing people: A poselet-based approach to attribute classification	[pdf]	[s2]		7808937b46acad36e43c30ae4e9f3fd57462853d
mapillary	Mapillary	The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes	The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes	[pdf]	[s2]		79828e6e9f137a583082b8b5a9dfce0c301989b8
nudedetection	Nude Detection	A Bag-of-Features Approach based on Hue-SIFT Descriptor for Nude Detection	A bag-of-features approach based on Hue-SIFT descriptor for nude detection	[pdf]	[s2]		7ace44190729927e5cb0dd5d363fcae966fe13f7
lfw	LFW	Labeled Faces in the Wild: A Survey	Labeled Faces in the Wild : A Survey	[pdf]	[s2]		7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22
vgg_celebs_in_places	CIP	Faces in Places: Compound Query Retrieval	Faces in Places: compound query retrieval	[pdf]	[s2]	University of Oxford	7ebb153704706e457ab57b432793d2b6e5d12592
nova_emotions	Novaemötions Dataset	Competitive affective gamming: Winning with a smile	Competitive affective gaming: winning with a smile	[pdf]	[s2]		7f4040b482d16354d5938c1d1b926b544652bf5b
sun_attributes	SUN	SUN Attribute Database: Discovering, Annotating, and Recognizing Scene Attributes	SUN attribute database: Discovering, annotating, and recognizing scene attributes	[pdf]	[s2]		833fa04463d90aab4a9fe2870d480f0b40df446e
svs	SVS	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	[pdf]	[s2]		488e475eeb3bb39a145f23ede197cd3620f1d98a
texas_3dfrd	Texas 3DFRD	Texas 3D Face Recognition Database	Texas 3D Face Recognition Database	[pdf]	[s2]		4d58f886f5150b2d5e48fd1b5a49e09799bf895d
texas_3dfrd	Texas 3DFRD	Anthropometric 3D Face Recognition	Anthropometric 3D Face Recognition	[pdf]	[s2]		2ce2560cf59db59ce313bbeb004e8ce55c5ce928
tiny_faces	TinyFace	Low-Resolution Face Recognition	Low-Resolution Face Recognition	[pdf]	[s2]		8990cdce3f917dad622e43e033db686b354d057c
tiny_images	Tiny Images	80 million tiny images: a large dataset for non-parametric object and scene recognition	80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition	[pdf]	[s2]		31b58ced31f22eab10bd3ee2d9174e7c14c27c01
towncenter	TownCenter	Stable Multi-Target Tracking in Real-Time Surveillance Video	Stable multi-target tracking in real-time surveillance video	[pdf]	[s2]		9361b784e73e9238d5cefbea5ac40d35d1e3103f
tud_brussels	TUD-Brussels	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]		6ad5a38df8dd4cdddd74f31996ce096d41219f72
tud_campus	TUD-Campus	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]		3316521a5527c7700af8ae6aef32a79a8b83672c
tud_crossing	TUD-Crossing	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]		3316521a5527c7700af8ae6aef32a79a8b83672c
tud_motionpairs	TUD-Motionparis	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]		6ad5a38df8dd4cdddd74f31996ce096d41219f72
tud_multiview	TUD-Multiview	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]		436f798d1a4e54e5947c1e7d7375c31b2bdb4064
tud_pedestrian	TUD-Pedestrian	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]		3316521a5527c7700af8ae6aef32a79a8b83672c
tud_stadtmitte	TUD-Stadtmitte	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]		436f798d1a4e54e5947c1e7d7375c31b2bdb4064
tvhi	TVHI	High Five: Recognising human interactions in TV shows	High Five: Recognising human interactions in TV shows	[pdf]	[s2]		3cd40bfa1ff193a96bde0207e5140a399476466c
uccs	UCCS	Large scale unconstrained open set face database	Large scale unconstrained open set face database	[pdf]	[s2]	University of Colorado at Colorado Springs	07fcbae86f7a3ad3ea1cf95178459ee9eaf77cb1
ucf_101	UCF101	UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild	UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild	[pdf]	[s2]	University of Central Florida	b5f2846a506fc417e7da43f6a7679146d99c5e96
ucf_crowd	UCF-CC-50	Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images	Multi-source Multi-scale Counting in Extremely Dense Crowd Images	[pdf]	[s2]		32c801cb7fbeb742edfd94cccfca4934baec71da
ucf_selfie	UCF Selfie	How to Take a Good Selfie?	How to Take a Good Selfie?	[pdf]	[s2]		041d3eedf5e45ce5c5229f0181c5c576ed1fafd6
ufdd	UFDD	Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results	Pushing the Limits of Unconstrained Face Detection: a Challenge Dataset and Baseline Results	[pdf]	[s2]	Johns Hopkins University	377f2b65e6a9300448bdccf678cde59449ecd337
umb	UMB	UMB-DB: A Database of Partially Occluded 3D Faces	UMB-DB: A database of partially occluded 3D faces	[pdf]	[s2]		16e8b0a1e8451d5f697b94c0c2b32a00abee1d52
umd_faces	UMD	UMDFaces: An Annotated Face Dataset for Training Deep Networks	UMDFaces: An annotated face dataset for training deep networks	[pdf]	[s2]		31b05f65405534a696a847dd19c621b7b8588263
umd_faces	UMD	The Do's and Don'ts for CNN-based Face Verification	The Do’s and Don’ts for CNN-Based Face Verification	[pdf]	[s2]		71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6
unbc_shoulder_pain	UNBC-McMaster Pain	PAINFUL DATA: The UNBC-McMaster Shoulder Pain Expression Archive Database	Painful data: The UNBC-McMaster shoulder pain expression archive database	[pdf]	[s2]		56ffa7d906b08d02d6d5a12c7377a57e24ef3391
urban_tribes	Urban Tribes	From Bikers to Surfers: Visual Recognition of Urban Tribes	From Bikers to Surfers: Visual Recognition of Urban Tribes	[pdf]	[s2]	Columbia University	774cbb45968607a027ae4729077734db000a1ec5
used	USED Social Event Dataset	USED: A Large-scale Social Event Detection Dataset	USED: a large-scale social event detection dataset	[pdf]	[s2]		8627f019882b024aef92e4eb9355c499c733e5b7
v47	V47	Re-identification of Pedestrians with Variable Occlusion and Scale	Re-identification of pedestrians with variable occlusion and scale	[pdf]	[s2]		922e0a51a3b8c67c4c6ac09a577ff674cbd28b34
vadana	VADANA	VADANA: A dense dataset for facial image analysis	VADANA: A dense dataset for facial image analysis	[pdf]	[s2]		4563b46d42079242f06567b3f2e2f7a80cb3befe
vgg_celebs_in_places	CIP	Faces in Places: Compound Query Retrieval	Faces in Places: compound query retrieval	[pdf]	[s2]	University of Oxford	7ebb153704706e457ab57b432793d2b6e5d12592
vgg_faces	VGG Face	Deep Face Recognition	Deep Face Recognition	[pdf]	[s2]		162ea969d1929ed180cc6de9f0bf116993ff6e06
vgg_faces2	VGG Face2	VGGFace2: A dataset for recognising faces across pose and age	VGGFace2: A Dataset for Recognising Faces across Pose and Age	[pdf]	[s2]	University of Oxford	eb027969f9310e0ae941e2adee2d42cdf07d938c
violent_flows	Violent Flows	Violent Flows: Real-Time Detection of Violent Crowd Behavior	Violent flows: Real-time detection of violent crowd behavior	[pdf]	[s2]		5194cbd51f9769ab25260446b4fa17204752e799
viper	VIPeR	Evaluating Appearance Models for Recognition, Reacquisition, and Tracking	Evaluating Appearance Models for Recognition , Reacquisition , and Tracking	[pdf]	[s2]		6273b3491e94ea4dd1ce42b791d77bdc96ee73a8
visual_phrases	Phrasal Recognition	Recognition using Visual Phrases	Recognition using visual phrases	[pdf]	[s2]		e8de844fefd54541b71c9823416daa238be65546
vmu	VMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]		37d6f0eb074d207b53885bd2eb78ccc8a04be597
voc	VOC	The PASCAL Visual Object Classes (VOC) Challenge	The Pascal Visual Object Classes (VOC) Challenge	[pdf]	[s2]		0ee1916a0cb2dc7d3add086b5f1092c3d4beb38a
vqa	VQA	VQA: Visual Question Answering	VQA: Visual Question Answering	[pdf]	[s2]		01959ef569f74c286956024866c1d107099199f7
ward	WARD	Re-identify people in wide area camera network	Re-identify people in wide area camera network	[pdf]	[s2]		6f3c76b7c0bd8e1d122c6ea808a271fd4749c951
who_goes_there	WGT	Who Goes There? Approaches to Mapping Facial Appearance Diversity	Who goes there?: approaches to mapping facial appearance diversity	[pdf]	[s2]		9b9bf5e623cb8af7407d2d2d857bc3f1b531c182
wider	WIDER	Recognize Complex Events from Static Images by Fusing Deep Channels	Recognize complex events from static images by fusing deep channels	[pdf]	[s2]	Shenzhen Institutes of Advanced Technology	356b431d4f7a2a0a38cf971c84568207dcdbf189
wider_attribute	WIDER Attribute	Human Attribute Recognition by Deep Hierarchical Contexts	Human Attribute Recognition by Deep Hierarchical Contexts	[pdf]	[s2]	Chinese University of Hong Kong	44d23df380af207f5ac5b41459c722c87283e1eb
wider_face	WIDER FACE	WIDER FACE: A Face Detection Benchmark	WIDER FACE: A Face Detection Benchmark	[pdf]	[s2]	Chinese University of Hong Kong	52d7eb0fbc3522434c13cc247549f74bb9609c5d
wildtrack	WildTrack	WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	[pdf]	[s2]		77c81c13a110a341c140995bedb98101b9e84f7f
wlfdb		WLFDB: Weakly Labeled Face Databases	WLFDB: Weakly Labeled Face Databases	[pdf]	[s2]		5ad4e9f947c1653c247d418f05dad758a3f9277b
yale_faces	YaleFaces	Acquiring Linear Subspaces for Face Recognition under Variable Lighting	Acquiring linear subspaces for face recognition under variable lighting	[pdf]	[s2]		2ad0ee93d029e790ebb50574f403a09854b65b7e
yale_faces	YaleFaces	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	[pdf]	[s2]		18c72175ddbb7d5956d180b65a96005c100f6014
yawdd	YawDD	YawDD: A Yawning Detection Dataset	YawDD: a yawning detection dataset	[pdf]	[s2]		a94cae786d515d3450d48267e12ca954aab791c4
yfcc_100m	YFCC100M	YFCC100M: The New Data in Multimedia Research	YFCC100M: the new data in multimedia research	[pdf]	[s2]		010f0f4929e6a6644fb01f0e43820f91d0fad292
york_3d	UOY 3D Face Database	Three-Dimensional Face Recognition: An Eigensurface Approach	Three-dimensional face recognition: an eigensurface approach	[pdf]	[s2]		19d1b811df60f86cbd5e04a094b07f32fff7a32a
youtube_faces	YouTubeFaces	Face Recognition in Unconstrained Videos with Matched Background Similarity	Face recognition in unconstrained videos with matched background similarity	[pdf]	[s2]	Open University of Israel	560e0e58d0059259ddf86fcec1fa7975dee6a868
youtube_makeup	YMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]		37d6f0eb074d207b53885bd2eb78ccc8a04be597
youtube_makeup	YMU	Automatic Facial Makeup Detection with Application in Face Recognition	Automatic facial makeup detection with application in face recognition	[pdf]	[s2]	West Virginia University	fcc6fe6007c322641796cb8792718641856a22a7
youtube_poses	YouTube Pose	Personalizing Human Video Pose Estimation	Personalizing Human Video Pose Estimation	[pdf]	[s2]		1c2802c2199b6d15ecefe7ba0c39bfe44363de38
gfw	YouTube Pose	Merge or Not? Learning to Group Faces via Imitation Learning	Merge or Not? Learning to Group Faces via Imitation Learning	[pdf]	[s2]		e58dd160a76349d46f881bd6ddbc2921f08d1050

\ No newline at end of file +discovering, annotating, and recognizing scene attributes&sort=relevance" target="_blank">[s2]

833fa04463d90aab4a9fe2870d480f0b40df446e

imdb_wiki

IMDB

DEX: Deep EXpectation of apparent age from a single image

DEX: Deep EXpectation of Apparent Age from a Single Image

[pdf]

[s2]

8355d095d3534ef511a9af68a3b2893339e3f96b

awe_ears

AWE Ears

Ear Recognition: More Than a Survey

[pdf]

[s2]

84fe5b4ac805af63206012d29523a1e033bc827e

casia_webface

CASIA Webface

Learning Face Representation from Scratch

[pdf]

[s2]

853bd61bc48a431b9b1c7cab10c603830c488e39

used

USED Social Event Dataset

USED: A Large-scale Social Event Detection Dataset

USED: a large-scale social event detection dataset

[pdf]

[s2]

8627f019882b024aef92e4eb9355c499c733e5b7

tiny_faces

TinyFace

Low-Resolution Face Recognition

[pdf]

[s2]

8990cdce3f917dad622e43e033db686b354d057c

mafl

MAFL

Facial Landmark Detection by Deep Multi-task Learning

[pdf]

[s2]

Chinese University of Hong Kong

8a3c5507237957d013a0fe0f082cab7f757af6ee

mtfl

MTFL

Facial Landmark Detection by Deep Multi-task Learning

[pdf]

[s2]

Chinese University of Hong Kong

8a3c5507237957d013a0fe0f082cab7f757af6ee

10k_US_adult_faces

10K US Adult Faces

The intrinsic memorability of face images

The intrinsic memorability of face photographs.

[pdf]

[s2]

8b2dd5c61b23ead5ae5508bb8ce808b5ea266730

fei

FEI

Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro

A new ranking method for principal components analysis and its application to face image analysis

[pdf]

[s2]

8b56e33f33e582f3e473dba573a16b598ed9bcdc

chalearn

ChaLearn

ChaLearn Looking at People: A Review of Events and Resources

ChaLearn looking at people: A review of events and resources

[pdf]

[s2]

8d5998cd984e7cce307da7d46f155f9db99c6590

hda_plus

HDA+

The HDA+ data set for research on fully automated re-identification systems

The HDA+ Data Set for Research on Fully Automated Re-identification Systems

[pdf]

[s2]

8f02ec0be21461fbcedf51d864f944cfc42c875f

morph

MORPH Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

morph_nc

MORPH Non-Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

v47

V47

Re-identification of Pedestrians with Variable Occlusion and Scale

Re-identification of pedestrians with variable occlusion and scale

[pdf]

[s2]

922e0a51a3b8c67c4c6ac09a577ff674cbd28b34

towncenter

TownCenter

Stable Multi-Target Tracking in Real-Time Surveillance Video

Stable multi-target tracking in real-time surveillance video

[pdf]

[s2]

9361b784e73e9238d5cefbea5ac40d35d1e3103f

helen

Helen

Interactive Facial Feature Localization

[pdf]

[s2]

University of Illinois, Urbana-Champaign

95f12d27c3b4914e0668a268360948bce92f7db3

4dfab

4DFAB

4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications

[pdf]

[s2]

9696ad8b164f5e10fcfe23aacf74bd6168aebb15

megaface

MegaFace

The MegaFace Benchmark: 1 Million Faces for Recognition at Scale

[pdf]

[s2]

University of Washington

96e0cfcd81cdeb8282e29ef9ec9962b125f379b0

ilids_vid_reid

iLIDS-VID

Person Re-Identication by Video Ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

sdu_vid

SDU-VID

Person reidentification by video ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

m2vts

The M2VTS Multimodal Face Database (Release 1.00)

[pdf]

[s2]

9a9877791945c6fa4c1743ec6d3fb32570ef8481

who_goes_there

WGT

Who Goes There? Approaches to Mapping Facial Appearance Diversity

Who goes there?: approaches to mapping facial appearance diversity

[pdf]

[s2]

9b9bf5e623cb8af7407d2d2d857bc3f1b531c182

facebook_100

Facebook100

Scaling Up Biologically-Inspired Computer Vision: A Case Study in Unconstrained Face Recognition on Facebook

Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook

[pdf]

[s2]

Harvard University

9c23859ec7313f2e756a3e85575735e0c52249f4

pubfig_83

pubfig83

Scaling Up Biologically-Inspired Computer Vision: A Case Study in Unconstrained Face Recognition on Facebook

Scaling up biologically-inspired computer vision: A case study in unconstrained face recognition on facebook

[pdf]

[s2]

Harvard University

9c23859ec7313f2e756a3e85575735e0c52249f4

precarious

Precarious

Expecting the Unexpected: Training Detectors for Unusual Pedestrians With Adversarial Imposters

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters

[pdf]

[s2]

9e5378e7b336c89735d3bb15cf67eff96f86d39a

mafl

MAFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

mtfl

MTFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

moments_in_time

Moments in Time

Moments in Time Dataset: one million videos for event understanding

[pdf]

[s2]

a5a44a32a91474f00a3cda671a802e87c899fbb4

aflw

AFLW

Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

market1203

Market 1203

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

pku_reid

PKU-Reid

Orientation driven bag of appearances for person re-identification

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

hi4d_adsip

Hi4D-ADSIP

Hi4D-ADSIP 3-D dynamic facial articulation database

[pdf]

[s2]

a8d0b149c2eadaa02204d3e4356fbc8eccf3b315

yawdd

YawDD

YawDD: A Yawning Detection Dataset

YawDD: a yawning detection dataset

[pdf]

[s2]

a94cae786d515d3450d48267e12ca954aab791c4

mrp_drone

MRP Drone

Investigating Open-World Person Re-identification Using a Drone

[pdf]

[s2]

ad01687649d95cd5b56d7399a9603c4b8e2217d7

put_face

Put Face

The PUT face database

The put face database

[pdf]

[s2]

ae0aee03d946efffdc7af2362a42d3750e7dd48a

afew_va

AFEW-VA

Collecting Large, Richly Annotated Facial-Expression Databases from Movies

[pdf]

[s2]

Australian National University

b1f4423c227fa37b9680787be38857069247a307

ucf_101

UCF101

UCF101: A Dataset of 101 Human Actions Classes From Videos in The Wild

[pdf]

[s2]

University of Central Florida

b5f2846a506fc417e7da43f6a7679146d99c5e96

m2vtsdb_extended

xm2vtsdb

XM2VTSDB: The Extended M2VTS Database

Xm2vtsdb: the Extended M2vts Database

[pdf]

[s2]

b62628ac06bbac998a3ab825324a41a11bc3a988

ifdb

IFDB

Iranian Face Database with age, pose and expression

[pdf]

[s2]

b71d1aa90dcbe3638888725314c0d56640c1fef1

bp4d_spontanous

BP4D-Spontanous

A high resolution spontaneous 3D dynamic facial expression database

A high-resolution spontaneous 3D dynamic facial expression database

[pdf]

[s2]

SUNY Binghamton

b91f54e1581fbbf60392364323d00a0cd43e493c

pornodb

Pornography DB

Pooling in Image Representation: the Visual Codeword Point of View

Pooling in image representation: The visual codeword point of view

[pdf]

[s2]

b92a1ed9622b8268ae3ac9090e25789fc41cc9b8

scut_fbp

SCUT-FBP

SCUT-FBP: A Benchmark Dataset for Facial Beauty Perception

[pdf]

[s2]

South China University of Technology

bd26dabab576adb6af30484183c9c9c8379bf2e0

hda_plus

HDA+

A Multi-camera video data set for research on High-Definition surveillance

HDA dataset-DRAFT 1 A Multi-camera video data set for research on High-Definition surveillance

[pdf]

[s2]

bd88bb2e4f351352d88ee7375af834360e223498

mars

MARS

MARS: A Video Benchmark for Large-Scale Person Re-identification

MARS: A Video Benchmark for Large-Scale Person Re-Identification

[pdf]

[s2]

c0387e788a52f10bf35d4d50659cfa515d89fbec

nova_emotions

Novaemötions Dataset

Crowdsourcing facial expressions for affective-interaction

[pdf]

[s2]

c06b13d0ec3f5c43e2782cd22542588e233733c3

mcgill

McGill Real World

Hierarchical Temporal Graphical Model for Head Pose Estimation and Subsequent Attribute Classification in Real-World Videos

Hierarchical temporal graphical model for head pose estimation and subsequent attribute classification in real-world videos

[pdf]

[s2]

a5a3bc3e5e9753769163cb30b16dbd12e266b93e

mcgill

McGill Real World

Robust Semi-automatic Head Pose Labeling for Real-World Face Video Sequences

Robust semi-automatic head pose labeling for real-world face video sequences

[pdf]

[s2]

McGill University

c570d1247e337f91e555c3be0e8c8a5aba539d9f

qmul_surv_face

QMUL-SurvFace

Surveillance Face Recognition Challenge

[pdf]

[s2]

c866a2afc871910e3282fd9498dce4ab20f6a332

emotio_net

EmotioNet Database

EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild

[pdf]

[s2]

c900e0ad4c95948baaf0acd8449fde26f9b4952a

imfdb

IMFDB

Indian Movie Face Database: A Benchmark for Face Recognition Under Wide Variations

Indian Movie Face Database: A benchmark for face recognition under wide variations

[pdf]

[s2]

ca3e88d87e1344d076c964ea89d91a75c417f5ee

bu_3dfe

BU-3DFE

A 3D Facial Expression Database For Facial Behavior Research

A 3D facial expression database for facial behavior research

[pdf]

[s2]

SUNY Binghamton

cc589c499dcf323fe4a143bbef0074c3e31f9b60

b3d_ac

B3D(AC)

A 3-D Audio-Visual Corpus of Affective Communication

[pdf]

[s2]

d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae

jiku_mobile

Jiku Mobile Video Dataset

The Jiku Mobile Video Dataset

The jiku mobile video dataset

[pdf]

[s2]

d178cde92ab3dc0dd2ebee5a76a33d556c39448b

stair_actions

STAIR Action

STAIR Actions: A Video Dataset of Everyday Home Actions

[pdf]

[s2]

d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9

megaage

MegaAge

Quantifying Facial Age by Posterior of Age Comparisons

[pdf]

[s2]

Chinese University of Hong Kong

d80a3d1f3a438e02a6685e66ee908446766fefa9

feret

FERET

The FERET database and evaluation procedure for face-recognition algorithms

[pdf]

[s2]

dc8b25e35a3acb812beb499844734081722319b4

families_in_the_wild

FIW

Visual Kinship Recognition of Families in the Wild

[pdf]

[s2]

dd65f71dac86e36eecbd3ed225d016c3336b4a13

scut_head

SCUT HEAD

Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture

[pdf]

[s2]

d3200d49a19a4a4e4e9745ee39649b65d80c834b

sarc3d

Sarc3D

SARC3D: a new 3D body model for People Tracking and Re-identification

SARC3D: A New 3D Body Model for People Tracking and Re-identification

[pdf]

[s2]

e27ef52c641c2b5100a1b34fd0b819e84a31b4df

fiw_300

300-W

300 faces In-the-wild challenge: Database and results

300 Faces In-The-Wild Challenge: database and results

[pdf]

[s2]

e4754afaa15b1b53e70743880484b8d0736990ff

gfw

YouTube Pose

Merge or Not? Learning to Group Faces via Imitation Learning

[pdf]

[s2]

e58dd160a76349d46f881bd6ddbc2921f08d1050

visual_phrases

Phrasal Recognition

Recognition using Visual Phrases

Recognition using visual phrases

[pdf]

[s2]

e8de844fefd54541b71c9823416daa238be65546

mpi_large

Large MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

mpi_small

Small MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

vgg_faces2

VGG Face2

VGGFace2: A dataset for recognising faces across pose and age

VGGFace2: A Dataset for Recognising Faces across Pose and Age

[pdf]

[s2]

University of Oxford

eb027969f9310e0ae941e2adee2d42cdf07d938c

msmt_17

MSMT17

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

[pdf]

[s2]

ec792ad2433b6579f2566c932ee414111e194537

europersons

EuroCity Persons

The EuroCity Persons Dataset: A Novel Benchmark for Object Detection

[pdf]

[s2]

f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4

mug_faces

MUG Faces

The MUG Facial Expression Database

The MUG facial expression database

[pdf]

[s2]

Aristotle University of Thessaloniki

f1af714b92372c8e606485a3982eab2f16772ad8

pku

PKU

Swiss-System Based Cascade Ranking for Gait-based Person Re-identification

Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification

[pdf]

[s2]

f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f

caltech_pedestrians

Caltech Pedestrians

Pedestrian Detection: An Evaluation of the State of the Art

[pdf]

[s2]

f72f6a45ee240cc99296a287ff725aaa7e7ebb35

iit_dehli_ear

IIT Dehli Ear

Automated human identification using ear imaging

Automated Human Identification Using Ear Imaging

[pdf]

[s2]

faf40ce28857aedf183e193486f5b4b0a8c478a2

miw

MIW

Automatic Facial Makeup Detection with Application in Face Recognition

Automatic facial makeup detection with application in face recognition

[pdf]

[s2]

West Virginia University

fcc6fe6007c322641796cb8792718641856a22a7

youtube_makeup

YMU

Automatic Facial Makeup Detection with Application in Face Recognition

Automatic facial makeup detection with application in face recognition

[pdf]

[s2]

West Virginia University

fcc6fe6007c322641796cb8792718641856a22a7

nd_2006

ND-2006

Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition

[pdf]

[s2]

fd8168f1c50de85bac58a8d328df0a50248b16ae

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Papers with no location

key

name

our title

found title

address

s2 id

10k_US_adult_faces

10K US Adult Faces

The intrinsic memorability of face images

The intrinsic memorability of face photographs.

[pdf]

[s2]

8b2dd5c61b23ead5ae5508bb8ce808b5ea266730

3d_rma

3D-RMA

Automatic 3D Face Authentication

Automatic 3D face authentication

[pdf]

[s2]

2160788824c4c29ffe213b2cbeb3f52972d73f37

3dddb_unconstrained

3D Dynamic

A 3D Dynamic Database for Unconstrained Face Recognition

A 3 D Dynamic Database for Unconstrained Face Recognition

[pdf]

[s2]

4d4bb462c9f1d4e4ab1e4aa6a75cc0bc71b38461

3dpes

3DPeS

3DPes: 3D People Dataset for Surveillance and Forensics

3DPeS: 3D people dataset for surveillance and forensics

[pdf]

[s2]

2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e

4dfab

4DFAB

4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications

[pdf]

[s2]

9696ad8b164f5e10fcfe23aacf74bd6168aebb15

50_people_one_question

50 People One Question

Merging Pose Estimates Across Space and Time

[pdf]

[s2]

5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725

a_pascal_yahoo

aPascal

Describing Objects by their Attributes

Describing objects by their attributes

[pdf]

[s2]

2e384f057211426ac5922f1b33d2aa8df5d51f57

adience

Adience

Age and Gender Estimation of Unfiltered Faces

[pdf]

[s2]

1be498d4bbc30c3bfd0029114c784bc2114d67c0

afad

AFAD

Ordinal Regression with a Multiple Output CNN for Age Estimation

Ordinal Regression with Multiple Output CNN for Age Estimation

[pdf]

[s2]

6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c

afew_va

AFEW-VA

AFEW-VA database for valence and arousal estimation in-the-wild

[pdf]

[s2]

2624d84503bc2f8e190e061c5480b6aa4d89277a

affectnet

AffectNet

AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild

[pdf]

[s2]

758d7e1be64cc668c59ef33ba8882c8597406e53

aflw

AFLW

Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

agedb

AgeDB

AgeDB: the first manually collected, in-the-wild age database

AgeDB: The First Manually Collected, In-the-Wild Age Database

[pdf]

[s2]

6dcf418c778f528b5792104760f1fbfe90c6dd6a

alert_airport

ALERT Airport

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.

[pdf]

[s2]

6403117f9c005ae81f1e8e6d1302f4a045e3d99d

am_fed

AM-FED

Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”

Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"

[pdf]

[s2]

47aeb3b82f54b5ae8142b4bdda7b614433e69b9a

apis

APiS1.0

Pedestrian Attribute Classification in Surveillance: Database and Evaluation

[pdf]

[s2]

488e475eeb3bb39a145f23ede197cd3620f1d98a

ar_facedb

AR Face

The AR Face Database

The AR face database

[pdf]

[s2]

6d96f946aaabc734af7fe3fc4454cf8547fcd5ed

awe_ears

AWE Ears

Ear Recognition: More Than a Survey

[pdf]

[s2]

84fe5b4ac805af63206012d29523a1e033bc827e

b3d_ac

B3D(AC)

A 3-D Audio-Visual Corpus of Affective Communication

[pdf]

[s2]

d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae

bbc_pose

BBC Pose

Automatic and Efficient Human Pose Estimation for Sign Language Videos

[pdf]

[s2]

213a579af9e4f57f071b884aa872651372b661fd

berkeley_pose

BPAD

Describing People: A Poselet-Based Approach to Attribute Classification

Describing people: A poselet-based approach to attribute classification

[pdf]

[s2]

7808937b46acad36e43c30ae4e9f3fd57462853d

bfm

BFM

A 3D Face Model for Pose and Illumination Invariant Face Recognition

[pdf]

[s2]

639937b3a1b8bded3f7e9a40e85bd3770016cf3c

bio_id

BioID Face

Robust Face Detection Using the Hausdorff Distance

[pdf]

[s2]

4053e3423fb70ad9140ca89351df49675197196a

bjut_3d

BJUT-3D

The BJUT-3D Large-Scale Chinese Face Database

A novel face recognition method based on 3D face model

[pdf]

[s2]

1ed1a49534ad8dd00f81939449f6389cfbc25321

bosphorus

The Bosphorus

Bosphorus Database for 3D Face Analysis

[pdf]

[s2]

2acf7e58f0a526b957be2099c10aab693f795973

bp4d_plus

BP4D+

Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis

[pdf]

[s2]

53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4

brainwash

Brainwash

Brainwash dataset

Brainwash: A Data System for Feature Engineering

[pdf]

[s2]

214c966d1f9c2a4b66f4535d9a0d4078e63a5867

buhmap_db

BUHMAP-DB

Facial Feature Tracking and Expression Recognition for Sign Language

Facial feature tracking and expression recognition for sign language

[pdf]

[s2]

014b8df0180f33b9fea98f34ae611c6447d761d2

cafe

CAFE

The Child Affective Facial Expression (CAFE) Set: Validity and reliability from untrained adults

The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults

[pdf]

[s2]

20388099cc415c772926e47bcbbe554e133343d1

caltech_10k_web_faces

Caltech 10K Web Faces

Pruning Training Sets for Learning of Object Categories

Pruning training sets for learning of object categories

[pdf]

[s2]

636b8ffc09b1b23ff714ac8350bb35635e49fa3c

caltech_pedestrians

Caltech Pedestrians

Pedestrian Detection: A Benchmark

Pedestrian detection: A benchmark

[pdf]

[s2]

1dc35905a1deff8bc74688f2d7e2f48fd2273275

caltech_pedestrians

Caltech Pedestrians

Pedestrian Detection: An Evaluation of the State of the Art

[pdf]

[s2]

f72f6a45ee240cc99296a287ff725aaa7e7ebb35

camel

CAMEL

CAMEL Dataset for Visual and Thermal Infrared Multiple Object Detection and Tracking

Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

[pdf]

[s2]

5801690199c1917fa58c35c3dead177c0b8f9f2d

cas_peal

CAS-PEAL

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

[pdf]

[s2]

2485c98aa44131d1a2f7d1355b1e372f2bb148ad

casablanca

Casablanca

Context-aware {CNNs} for person head detection

Context-Aware CNNs for Person Head Detection

[pdf]

[s2]

0ceda9dae8b9f322df65ca2ef02caca9758aec6f

casia_webface

CASIA Webface

Learning Face Representation from Scratch

[pdf]

[s2]

853bd61bc48a431b9b1c7cab10c603830c488e39

cfd

CFD

The Chicago face database: A free stimulus set of faces and norming data

The Chicago face database: A free stimulus set of faces and norming data.

[pdf]

[s2]

4df3143922bcdf7db78eb91e6b5359d6ada004d2

chalearn

ChaLearn

ChaLearn Looking at People: A Review of Events and Resources

ChaLearn looking at people: A review of events and resources

[pdf]

[s2]

8d5998cd984e7cce307da7d46f155f9db99c6590

cityscapes

Cityscapes

The Cityscapes Dataset for Semantic Urban Scene Understanding

[pdf]

[s2]

32cde90437ab5a70cf003ea36f66f2de0e24b3ab

cityscapes

Cityscapes

The Cityscapes Dataset

[pdf]

[s2]

5ffd74d2873b7cba2cbc5fd295cc7fbdedca22a2

clothing_co_parsing

CCP

Clothing Co-Parsing by Joint Image Segmentation and Labeling

Clothing Co-parsing by Joint Image Segmentation and Labeling

[pdf]

[s2]

2bf8541199728262f78d4dced6fb91479b39b738

cmu_pie

CMU PIE

The CMU Pose, Illumination, and Expression Database

The CMU Pose, Illumination, and Expression (PIE) Database

[pdf]

[s2]

4d423acc78273b75134e2afd1777ba6d3a398973

coco

COCO

Microsoft COCO: Common Objects in Context

[pdf]

[s2]

5e0f8c355a37a5a89351c02f174e7a5ddcb98683

coco_action

COCO-a

Describing Common Human Visual Actions in Images

[pdf]

[s2]

4946ba10a4d5a7d0a38372f23e6622bd347ae273

coco_qa

COCO QA

Exploring Models and Data for Image Question Answering

[pdf]

[s2]

35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62

cofw

COFW

Robust face landmark estimation under occlusion

Robust Face Landmark Estimation under Occlusion

[pdf]

[s2]

2724ba85ec4a66de18da33925e537f3902f21249

cohn_kanade_plus

CK+

The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression

[pdf]

[s2]

4d9a02d080636e9666c4d1cc438b9893391ec6c7

columbia_gaze

Columbia Gaze

Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction

Gaze locking: passive eye contact detection for human-object interaction

[pdf]

[s2]

06f02199690961ba52997cde1527e714d2b3bf8f

complex_activities

Ongoing Complex Activities

Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space

Recognition of ongoing complex activities by sequence prediction over a hierarchical label space

[pdf]

[s2]

65355cbb581a219bd7461d48b3afd115263ea760

cuhk01

CUHK01

Human Reidentification with Transferred Metric Learning

[pdf]

[s2]

44484d2866f222bbb9b6b0870890f9eea1ffb2d0

cuhk02

CUHK02

Locally Aligned Feature Transforms across Views

[pdf]

[s2]

38b55d95189c5e69cf4ab45098a48fba407609b4

cuhk03

CUHK03

DeepReID: Deep Filter Pairing Neural Network for Person Re-identification

[pdf]

[s2]

6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3

cvc_01_barcelona

CVC-01

Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection

Adaptive Image Sampling and Windows Classification for On – board Pedestrian Detection

[pdf]

[s2]

57fe081950f21ca03b5b375ae3e84b399c015861

czech_news_agency

UFI

Unconstrained Facial Images: Database for Face Recognition under Real-world Conditions

Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions

[pdf]

[s2]

4b4106614c1d553365bad75d7866bff0de6056ed

dartmouth_children

Dartmouth Children

The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set

The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set

[pdf]

[s2]

4e6ee936eb50dd032f7138702fa39b7c18ee8907

data_61

Data61 Pedestrian

A Multi-Modal Graphical Model for Scene Analysis

A Multi-modal Graphical Model for Scene Analysis

[pdf]

[s2]

563c940054e4b456661762c1ab858e6f730c3159

deep_fashion

DeepFashion

DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations

[pdf]

[s2]

18010284894ed0edcca74e5bf768ee2e15ef7841

disfa

DISFA

DISFA: A Spontaneous Facial Action Intensity Database

Extended DISFA Dataset: Investigating Posed and Spontaneous Facial Expressions

[pdf]

[s2]

a5acda0e8c0937bfed013e6382da127103e41395

distance_nighttime

Long Distance Heterogeneous Face

Nighttime Face Recognition at Long Distance: Cross-distance and Cross-spectral Matching

Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching

[pdf]

[s2]

4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06

duke_mtmc

Duke MTMC

Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking

[pdf]

[s2]

27a2fad58dd8727e280f97036e0d2bc55ef5424c

emotio_net

EmotioNet Database

EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild

[pdf]

[s2]

c900e0ad4c95948baaf0acd8449fde26f9b4952a

eth_andreas_ess

ETHZ Pedestrian

Depth and Appearance for Mobile Scene Analysis

[pdf]

[s2]

13f06b08f371ba8b5d31c3e288b4deb61335b462

europersons

EuroCity Persons

The EuroCity Persons Dataset: A Novel Benchmark for Object Detection

[pdf]

[s2]

f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4

expw

ExpW

From Facial Expression Recognition to Interpersonal Relation Prediction

[pdf]

[s2]

22f656d0f8426c84a33a267977f511f127bfd7f3

faceplace

Face Place

Recognizing disguised faces

[pdf]

[s2]

25474c21613607f6bb7687a281d5f9d4ffa1f9f3

families_in_the_wild

FIW

Visual Kinship Recognition of Families in the Wild

[pdf]

[s2]

dd65f71dac86e36eecbd3ed225d016c3336b4a13

fei

FEI

Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro

Generalização cartográfica automatizada para um banco de dados cadastral

[pdf]

[s2]

b6b1b0632eb9d4ab1427278f5e5c46f97753c73d

feret

FERET

The FERET Verification Testing Protocol for Face Recognition Algorithms

[pdf]

[s2]

0c4a139bb87c6743c7905b29a3cfec27a5130652

feret

FERET

The FERET database and evaluation procedure for face-recognition algorithms

[pdf]

[s2]

dc8b25e35a3acb812beb499844734081722319b4

feret

FERET

FERET ( Face Recognition Technology ) Recognition Algorithm Development and Test Results

[pdf]

[s2]

31de9b3dd6106ce6eec9a35991b2b9083395fd0b

feret

FERET

The FERET Evaluation Methodology for Face-Recognition Algorithms

[pdf]

[s2]

0f0fcf041559703998abf310e56f8a2f90ee6f21

ferplus

FER+

Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution

Training deep networks for facial expression recognition with crowd-sourced label distribution

[pdf]

[s2]

298cbc3dfbbb3a20af4eed97906650a4ea1c29e0

fia

CMU FiA

The CMU Face In Action (FIA) Database

[pdf]

[s2]

47662d1a368daf70ba70ef2d59eb6209f98b675d

fiw_300

300-W

300 faces In-the-wild challenge: Database and results

300 Faces In-The-Wild Challenge: database and results

[pdf]

[s2]

e4754afaa15b1b53e70743880484b8d0736990ff

frav3d

FRAV3D

MULTIMODAL 2D, 2.5D & 3D FACE VERIFICATION

Multimodal 2D, 2.5D & 3D Face Verification

[pdf]

[s2]

2b926b3586399d028b46315d7d9fb9d879e4f79c

frgc

FRGC

Overview of the Face Recognition Grand Challenge

Overview of the face recognition grand challenge

[pdf]

[s2]

18ae7c9a4bbc832b8b14bc4122070d7939f5e00e

gallagher

Gallagher

Clothing Cosegmentation for Recognizing People

Clothing cosegmentation for recognizing people

[pdf]

[s2]

22ad2c8c0f4d6aa4328b38d894b814ec22579761

gavab_db

Gavab

GavabDB: a 3D face database

Expression invariant 3D face recognition with a Morphable Model

[pdf]

[s2]

42505464808dfb446f521fc6ff2cfeffd4d68ff1

georgia_tech_face_database

Georgia Tech Face

Maximum likelihood training of the embedded HMM for face detection and recognition

[pdf]

[s2]

3dc3f0b64ef80f573e3a5f96e456e52ee980b877

graz

Graz Pedestrian

Generic Object Recognition with Boosting

Generic object recognition with boosting

[pdf]

[s2]

2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9

graz

Graz Pedestrian

Weak Hypotheses and Boosting for Generic Object Detection and Recognition

[pdf]

[s2]

0c91808994a250d7be332400a534a9291ca3b60e

graz

Graz Pedestrian

Object Recognition Using Segmentation for Feature Detection

Object recognition using segmentation for feature detection

[pdf]

[s2]

12ad3b5bbbf407f8e54ea692c07633d1a867c566

h3d

H3D

Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations

Poselets: Body part detectors trained using 3D human pose annotations

[pdf]

[s2]

2830fb5282de23d7784b4b4bc37065d27839a412

hda_plus

HDA+

The HDA+ data set for research on fully automated re-identification systems

The HDA+ Data Set for Research on Fully Automated Re-identification Systems

[pdf]

[s2]

8f02ec0be21461fbcedf51d864f944cfc42c875f

hda_plus

HDA+

A Multi-camera video data set for research on High-Definition surveillance

HDA dataset-DRAFT 1 A Multi-camera video data set for research on High-Definition surveillance

[pdf]

[s2]

bd88bb2e4f351352d88ee7375af834360e223498

hi4d_adsip

Hi4D-ADSIP

Hi4D-ADSIP 3-D dynamic facial articulation database

High-resolution comprehensive 3-D dynamic database for facial articulation analysis

[pdf]

[s2]

24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd

hollywood_headset

HollywoodHeads

Context-aware CNNs for person head detection

Context-Aware CNNs for Person Head Detection

[pdf]

[s2]

0ceda9dae8b9f322df65ca2ef02caca9758aec6f

hrt_transgender

HRT Transgender

Face recognition across gender transformation using SVM Classifier

Face recognition: A literature survey

[pdf]

[s2]

28312c3a47c1be3a67365700744d3d6665b86f22

ifad

IFAD

Indian Face Age Database: A Database for Face Recognition with Age Variation

Indian Face Age Database : A Database for Face Recognition with Age Variation

[pdf]

[s2]

55c40cbcf49a0225e72d911d762c27bb1c2d14aa

ifdb

IFDB

Iranian Face Database with age, pose and expression

[pdf]

[s2]

b71d1aa90dcbe3638888725314c0d56640c1fef1

ifdb

IFDB

Iranian Face Database and Evaluation with a New Detection Algorithm

[pdf]

[s2]

066d71fcd997033dce4ca58df924397dfe0b5fd1

iit_dehli_ear

IIT Dehli Ear

Automated human identification using ear imaging

Automated Human Identification Using Ear Imaging

[pdf]

[s2]

faf40ce28857aedf183e193486f5b4b0a8c478a2

ijb_c

IJB-A

Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A

Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A

[pdf]

[s2]

140c95e53c619eac594d70f6369f518adfea12ef

ijb_c

IJB-B

IARPA Janus Benchmark-B Face Dataset

[pdf]

[s2]

0cb2dd5f178e3a297a0c33068961018659d0f443

ijb_c

IJB-C

IARPA Janus Benchmark C

IARPA Janus Benchmark - C: Face Dataset and Protocol

[pdf]

[s2]

57178b36c21fd7f4529ac6748614bb3374714e91

ilids_mcts

Imagery Library for Intelligent Detection Systems: The i-LIDS User Guide

Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems

[pdf]

[s2]

0297448f3ed948e136bb06ceff10eccb34e5bb77

ilids_vid_reid

iLIDS-VID

Person Re-Identication by Video Ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

images_of_groups

Images of Groups

Understanding Groups of Images of People

Understanding images of groups of people

[pdf]

[s2]

21d9d0deed16f0ad62a4865e9acf0686f4f15492

imdb_wiki

IMDB

Deep expectation of real and apparent age from a single image without facial landmarks

Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks

[pdf]

[s2]

10195a163ab6348eef37213a46f60a3d87f289c5

imdb_wiki

IMDB

DEX: Deep EXpectation of apparent age from a single image

DEX: Deep EXpectation of Apparent Age from a Single Image

[pdf]

[s2]

8355d095d3534ef511a9af68a3b2893339e3f96b

imfdb

IMFDB

Indian Movie Face Database: A Benchmark for Face Recognition Under Wide Variations

Indian Movie Face Database: A benchmark for face recognition under wide variations

[pdf]

[s2]

ca3e88d87e1344d076c964ea89d91a75c417f5ee

imm_face

IMM Face Dataset

The IMM Face Database - An Annotated Dataset of 240 Face Images

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

immediacy

Immediacy

Multi-task Recurrent Neural Network for Immediacy Prediction

[pdf]

[s2]

1e3df3ca8feab0b36fd293fe689f93bb2aaac591

inria_person

INRIA Pedestrian

Histograms of Oriented Gradients for Human Detection

Histograms of oriented gradients for human detection

[pdf]

[s2]

10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5

jiku_mobile

Jiku Mobile Video Dataset

The Jiku Mobile Video Dataset

The jiku mobile video dataset

[pdf]

[s2]

d178cde92ab3dc0dd2ebee5a76a33d556c39448b

jpl_pose

JPL-Interaction dataset

First-Person Activity Recognition: What Are They Doing to Me?

[pdf]

[s2]

1aad2da473888cb7ebc1bfaa15bfa0f1502ce005

kdef

KDEF

The Karolinska Directed Emotional Faces – KDEF

Gaze fixation and the neural circuitry of face processing in autism

[pdf]

[s2]

93884e46c49f7ae1c7c34046fbc28882f2bd6341

kin_face

UB KinFace

Kinship Verification through Transfer Learning

[pdf]

[s2]

4793f11fbca4a7dba898b9fff68f70d868e2497c

kin_face

UB KinFace

Understanding Kin Relationships in a Photo

[pdf]

[s2]

08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7

kinectface

KinectFaceDB

KinectFaceDB: A Kinect Database for Face Recognition

[pdf]

[s2]

0b440695c822a8e35184fb2f60dcdaa8a6de84ae

kitti

KITTI

Vision meets Robotics: The KITTI Dataset

The Role of Machine Vision for Intelligent Vehicles

[pdf]

[s2]

35ba4ebfd017a56b51e967105af9ae273c9b0178

lag

LAG

Large Age-Gap Face Verification by Feature Injection in Deep Networks

Large age-gap face verification by feature injection in deep networks

[pdf]

[s2]

0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e

large_scale_person_search

Large Scale Person Search

End-to-End Deep Learning for Person Search

[pdf]

[s2]

2161f6b7ee3c0acc81603b01dc0df689683577b9

leeds_sports_pose

Leeds Sports Pose

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

[pdf]

[s2]

4b1d23d17476fcf78f4cbadf69fb130b1aa627c0

leeds_sports_pose_extended

Leeds Sports Pose Extended

Learning Effective Human Pose Estimation from Inaccurate Annotation

Learning effective human pose estimation from inaccurate annotation

[pdf]

[s2]

4e4746094bf60ee83e40d8597a6191e463b57f76

lfw

LFW

Labeled Faces in the Wild: A Survey

Labeled Faces in the Wild : A Survey

[pdf]

[s2]

7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22

lfw

LFW

Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

lfw_a

LFW-a

Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics

[pdf]

[s2]

133f01aec1534604d184d56de866a4bd531dac87

m2vts

The M2VTS Multimodal Face Database (Release 1.00)

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

[pdf]

[s2]

2485c98aa44131d1a2f7d1355b1e372f2bb148ad

m2vtsdb_extended

xm2vtsdb

XM2VTSDB: The Extended M2VTS Database

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

mafl

MAFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

mapillary

Mapillary

The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes

[pdf]

[s2]

79828e6e9f137a583082b8b5a9dfce0c301989b8

market_1501

Market 1501

Scalable Person Re-identification: A Benchmark

[pdf]

[s2]

4308bd8c28e37e2ed9a3fcfe74d5436cce34b410

market1203

Market 1203

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

mars

MARS

MARS: A Video Benchmark for Large-Scale Person Re-identification

MARS: A Video Benchmark for Large-Scale Person Re-Identification

[pdf]

[s2]

c0387e788a52f10bf35d4d50659cfa515d89fbec

megaface

MegaFace

Level Playing Field for Million Scale Face Recognition

[pdf]

[s2]

28d4e027c7e90b51b7d8908fce68128d1964668a

mit_cbcl

MIT CBCL

Component-based Face Recognition with 3D Morphable Models

Component-Based Face Recognition with 3D Morphable Models

[pdf]

[s2]

079a0a3bf5200994e1f972b1b9197bf2f90e87d4

mmi_facial_expression

MMI Facial Expression Dataset

WEB-BASED DATABASE FOR FACIAL EXPRESSION ANALYSIS

Web-based database for facial expression analysis

[pdf]

[s2]

2a75f34663a60ab1b04a0049ed1d14335129e908

moments_in_time

Moments in Time

Moments in Time Dataset: one million videos for event understanding

[pdf]

[s2]

a5a44a32a91474f00a3cda671a802e87c899fbb4

morph

MORPH Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

morph_nc

MORPH Non-Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

mot

MOT

Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mot

MOT

Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mot

MOT

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mpi_large

Large MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

mpi_small

Small MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

mpii_human_pose

MPII Human Pose

2D Human Pose Estimation: New Benchmark and State of the Art Analysis

[pdf]

[s2]

3325860c0c82a93b2eac654f5324dd6a776f609e

mr2

MR2

The MR2: A multi-racial mega-resolution database of facial stimuli

The MR2: A multi-racial, mega-resolution database of facial stimuli.

[pdf]

[s2]

578d4ad74818086bb64f182f72e2c8bd31e3d426

mrp_drone

MRP Drone

Investigating Open-World Person Re-identification Using a Drone

[pdf]

[s2]

ad01687649d95cd5b56d7399a9603c4b8e2217d7

msceleb

MsCeleb

MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition

[pdf]

[s2]

291265db88023e92bb8c8e6390438e5da148e8f5

msmt_17

MSMT17

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

[pdf]

[s2]

ec792ad2433b6579f2566c932ee414111e194537

mtfl

MTFL

Facial Landmark Detection by Deep Multi-task Learning

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

mtfl

MTFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

muct

MUCT

The MUCT Landmarked Face Database

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

multi_pie

MULTIPIE

Multi-PIE

Scheduling heterogeneous multi-cores through performance impact estimation (PIE)

[pdf]

[s2]

109df0e8e5969ddf01e073143e83599228a1163f

names_and_faces_news

News Dataset

Names and Faces

Names and faces in the news

[pdf]

[s2]

2fda164863a06a92d3a910b96eef927269aeb730

nd_2006

ND-2006

Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition

[pdf]

[s2]

fd8168f1c50de85bac58a8d328df0a50248b16ae

nova_emotions

Novaemötions Dataset

Crowdsourcing facial expressions for affective-interaction

[pdf]

[s2]

c06b13d0ec3f5c43e2782cd22542588e233733c3

nova_emotions

Novaemötions Dataset

Competitive affective gamming: Winning with a smile

Competitive affective gaming: winning with a smile

[pdf]

[s2]

7f4040b482d16354d5938c1d1b926b544652bf5b

nudedetection

Nude Detection

A Bag-of-Features Approach based on Hue-SIFT Descriptor for Nude Detection

A bag-of-features approach based on Hue-SIFT descriptor for nude detection

[pdf]

[s2]

7ace44190729927e5cb0dd5d363fcae966fe13f7

orl

ORL

Parameterisation of a Stochastic Model for Human Face Identification

Parameterisation of a stochastic model for human face identification

[pdf]

[s2]

55206f0b5f57ce17358999145506cd01e570358c

penn_fudan

Penn Fudan

Object Detection Combining Recognition and Segmentation

[pdf]

[s2]

3394168ff0719b03ff65bcea35336a76b21fe5e4

peta

PETA

Pedestrian Attribute Recognition At Far Distance

[pdf]

[s2]

2a4bbee0b4cf52d5aadbbc662164f7efba89566c

pets

PETS 2017

PETS 2017: Dataset and Challenge

[pdf]

[s2]

22909dd19a0ec3b6065334cb5be5392cb24d839d

pilot_parliament

PPB

Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classication

Summary of Research on Informant Accuracy in Network Data, 11 and on the Reverse Small World Problem

[pdf]

[s2]

fb82681ac5d3487bd8e52dbb3d1fa220eeac855e

pipa

PIPA

Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues

Beyond frontal faces: Improving Person Recognition using multiple cues

[pdf]

[s2]

0a85bdff552615643dd74646ac881862a7c7072d

pku

PKU

Swiss-System Based Cascade Ranking for Gait-based Person Re-identification

Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification

[pdf]

[s2]

f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f

pku_reid

PKU-Reid

Orientation driven bag of appearances for person re-identification

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

pornodb

Pornography DB

Pooling in Image Representation: the Visual Codeword Point of View

Pooling in image representation: The visual codeword point of view

[pdf]

[s2]

b92a1ed9622b8268ae3ac9090e25789fc41cc9b8

precarious

Precarious

Expecting the Unexpected: Training Detectors for Unusual Pedestrians With Adversarial Imposters

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters

[pdf]

[s2]

9e5378e7b336c89735d3bb15cf67eff96f86d39a

prid

PRID

Person Re-Identification by Descriptive and Discriminative Classification

Person Re-identification by Descriptive and Discriminative Classification

[pdf]

[s2]

16c7c31a7553d99f1837fc6e88e77b5ccbb346b8

psu

PSU

Vision-based Analysis of Small Groups in Pedestrian Crowds

Vision-Based Analysis of Small Groups in Pedestrian Crowds

[pdf]

[s2]

066000d44d6691d27202896691f08b27117918b9

put_face

Put Face

The PUT face database

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

qmul_grid

GRID

Multi-Camera Activity Correlation Analysis

Multi-camera activity correlation analysis

[pdf]

[s2]

3b5b6d19d4733ab606c39c69a889f9e67967f151

qmul_grid

GRID

Time-delayed correlation analysis for multi-camera activity understanding

Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding

[pdf]

[s2]

2edb87494278ad11641b6cf7a3f8996de12b8e14

qmul_surv_face

QMUL-SurvFace

Surveillance Face Recognition Challenge

[pdf]

[s2]

c866a2afc871910e3282fd9498dce4ab20f6a332

rafd

RaFD

Presentation and validation of the Radboud Faces Database

[pdf]

[s2]

3765df816dc5a061bc261e190acc8bdd9d47bec0

raid

RAiD

Consistent Re-identification in a Camera Network

[pdf]

[s2]

09d78009687bec46e70efcf39d4612822e61cb8c

rap_pedestrian

RAP

A Richly Annotated Dataset for Pedestrian Attribute Recognition

[pdf]

[s2]

221c18238b829c12b911706947ab38fd017acef7

reseed

ReSEED

ReSEED: Social Event dEtection Dataset

ReSEED: social event dEtection dataset

[pdf]

[s2]

54983972aafc8e149259d913524581357b0f91c3

saivt

SAIVT SoftBio

A Database for Person Re-Identification in Multi-Camera Surveillance Networks

[pdf]

[s2]

22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b

sarc3d

Sarc3D

SARC3D: a new 3D body model for People Tracking and Re-identification

SARC3D: A New 3D Body Model for People Tracking and Re-identification

[pdf]

[s2]

e27ef52c641c2b5100a1b34fd0b819e84a31b4df

scface

SCface

SCface – surveillance cameras face database

Large Variability Surveillance Camera Face Database

[pdf]

[s2]

f3b84a03985de3890b400b68e2a92c0a00afd9d0

scut_head

SCUT HEAD

Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture

[pdf]

[s2]

d3200d49a19a4a4e4e9745ee39649b65d80c834b

sdu_vid

SDU-VID

A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification

[pdf]

[s2]

3b4ec8af470948a72a6ed37a9fd226719a874ebc

sdu_vid

SDU-VID

Local descriptors encoded by Fisher vectors for person re-identification

Local Descriptors Encoded by Fisher Vectors for Person Re-identification

[pdf]

[s2]

46a01565e6afe7c074affb752e7069ee3bf2e4ef

sdu_vid

SDU-VID

Person reidentification by video ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

sheffield

Sheffield Face

Face Recognition: From Theory to Applications

Face Description with Local Binary Patterns: Application to Face Recognition

[pdf]

[s2]

3607afdb204de9a5a9300ae98aa4635d9effcda2

social_relation

Social Relation

From Facial Expression Recognition to Interpersonal Relation Prediction

[pdf]

[s2]

22f656d0f8426c84a33a267977f511f127bfd7f3

soton

SOTON HiD

On a Large Sequence-Based Human Gait Database

On a large sequence-based human gait database

[pdf]

[s2]

4f93cd09785c6e77bf4bc5a788e079df524c8d21

stair_actions

STAIR Action

STAIR Actions: A Video Dataset of Everyday Home Actions

[pdf]

[s2]

d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9

stanford_drone

Stanford Drone

Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes

Social LSTM: Human Trajectory Prediction in Crowded Spaces

[pdf]

[s2]

570f37ed63142312e6ccdf00ecc376341ec72b9f

stickmen_buffy

Buffy Stickmen

Learning to Parse Images of Articulated Objects

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

stickmen_buffy

Buffy Stickmen

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

[pdf]

[s2]

4b1d23d17476fcf78f4cbadf69fb130b1aa627c0

stickmen_family

We Are Family Stickmen

We Are Family: Joint Pose Estimation of Multiple Persons

[pdf]

[s2]

0dc11a37cadda92886c56a6fb5191ded62099c28

stickmen_pascal

Stickmen PASCAL

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

stickmen_pascal

Stickmen PASCAL

Learning to Parse Images of Articulated Objects

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

sun_attributes

SUN

The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding

[pdf]

[s2]

66e6f08873325d37e0ec20a4769ce881e04e964e

sun_attributes

SUN

SUN Attribute Database: +Papers with no location

Papers with no location

key	name	our title	found title			s2 id
yfcc_100m	YFCC100M	YFCC100M: The New Data in Multimedia Research	YFCC100M: the new data in multimedia research	[pdf]	[s2]	010f0f4929e6a6644fb01f0e43820f91d0fad292
buhmap_db	BUHMAP-DB	Facial Feature Tracking and Expression Recognition for Sign Language	Facial feature tracking and expression recognition for sign language	[pdf]	[s2]	014b8df0180f33b9fea98f34ae611c6447d761d2
vqa	VQA	VQA: Visual Question Answering	VQA: Visual Question Answering	[pdf]	[s2]	01959ef569f74c286956024866c1d107099199f7
kitti	KITTI	Vision meets Robotics: The KITTI Dataset	Vision meets robotics: The KITTI dataset	[pdf]	[s2]	026e3363b7f76b51cc711886597a44d5f1fd1de2
ilids_mcts	i-LIDS	Imagery Library for Intelligent Detection Systems: The i-LIDS User Guide	Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems	[pdf]	[s2]	0297448f3ed948e136bb06ceff10eccb34e5bb77
ucf_selfie	UCF Selfie	How to Take a Good Selfie?	How to Take a Good Selfie?	[pdf]	[s2]	041d3eedf5e45ce5c5229f0181c5c576ed1fafd6
psu	PSU	Vision-based Analysis of Small Groups in Pedestrian Crowds	Vision-Based Analysis of Small Groups in Pedestrian Crowds	[pdf]	[s2]	066000d44d6691d27202896691f08b27117918b9
ifdb	IFDB	Iranian Face Database and Evaluation with a New Detection Algorithm	Iranian Face Database and Evaluation with a New Detection Algorithm	[pdf]	[s2]	066d71fcd997033dce4ca58df924397dfe0b5fd1
columbia_gaze	Columbia Gaze	Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction	Gaze locking: passive eye contact detection for human-object interaction	[pdf]	[s2]	06f02199690961ba52997cde1527e714d2b3bf8f
mit_cbcl	MIT CBCL	Component-based Face Recognition with 3D Morphable Models	Component-Based Face Recognition with 3D Morphable Models	[pdf]	[s2]	079a0a3bf5200994e1f972b1b9197bf2f90e87d4
kin_face	UB KinFace	Understanding Kin Relationships in a Photo	Understanding Kin Relationships in a Photo	[pdf]	[s2]	08f6745bc6c1b0fb68953ea61054bdcdde6d2fc7
raid	RAiD	Consistent Re-identification in a Camera Network	Consistent Re-identification in a Camera Network	[pdf]	[s2]	09d78009687bec46e70efcf39d4612822e61cb8c
pipa	PIPA	Beyond Frontal Faces: Improving Person Recognition Using Multiple Cues	Beyond frontal faces: Improving Person Recognition using multiple cues	[pdf]	[s2]	0a85bdff552615643dd74646ac881862a7c7072d
kinectface	KinectFaceDB	KinectFaceDB: A Kinect Database for Face Recognition	KinectFaceDB: A Kinect Database for Face Recognition	[pdf]	[s2]	0b440695c822a8e35184fb2f60dcdaa8a6de84ae
feret	FERET	The FERET Verification Testing Protocol for Face Recognition Algorithms	The FERET Verification Testing Protocol for Face Recognition Algorithms	[pdf]	[s2]	0c4a139bb87c6743c7905b29a3cfec27a5130652
graz	Graz Pedestrian	Weak Hypotheses and Boosting for Generic Object Detection and Recognition	Weak Hypotheses and Boosting for Generic Object Detection and Recognition	[pdf]	[s2]	0c91808994a250d7be332400a534a9291ca3b60e
ijb_c	IJB-B	IARPA Janus Benchmark-B Face Dataset	IARPA Janus Benchmark-B Face Dataset	[pdf]	[s2]	0cb2dd5f178e3a297a0c33068961018659d0f443
casablanca	Casablanca	Context-aware {CNNs} for person head detection	Context-Aware CNNs for Person Head Detection	[pdf]	[s2]	0ceda9dae8b9f322df65ca2ef02caca9758aec6f
hollywood_headset	HollywoodHeads	Context-aware CNNs for person head detection	Context-Aware CNNs for Person Head Detection	[pdf]	[s2]	0ceda9dae8b9f322df65ca2ef02caca9758aec6f
lag	LAG	Large Age-Gap Face Verification by Feature Injection in Deep Networks	Large age-gap face verification by feature injection in deep networks	[pdf]	[s2]	0d2dd4fc016cb6a517d8fb43a7cc3ff62964832e
stickmen_family	We Are Family Stickmen	We Are Family: Joint Pose Estimation of Multiple Persons	We Are Family: Joint Pose Estimation of Multiple Persons	[pdf]	[s2]	0dc11a37cadda92886c56a6fb5191ded62099c28
voc	VOC	The PASCAL Visual Object Classes (VOC) Challenge	The Pascal Visual Object Classes (VOC) Challenge	[pdf]	[s2]	0ee1916a0cb2dc7d3add086b5f1092c3d4beb38a
feret	FERET	The FERET Evaluation Methodology for Face-Recognition Algorithms	The FERET Evaluation Methodology for Face-Recognition Algorithms	[pdf]	[s2]	0f0fcf041559703998abf310e56f8a2f90ee6f21
imdb_wiki	IMDB	Deep expectation of real and apparent age from a single image without facial landmarks	Deep Expectation of Real and Apparent Age from a Single Image Without Facial Landmarks	[pdf]	[s2]	10195a163ab6348eef37213a46f60a3d87f289c5
inria_person	INRIA Pedestrian	Histograms of Oriented Gradients for Human Detection	Histograms of oriented gradients for human detection	[pdf]	[s2]	10d6b12fa07c7c8d6c8c3f42c7f1c061c131d4c5
graz	Graz Pedestrian	Object Recognition Using Segmentation for Feature Detection	Object recognition using segmentation for feature detection	[pdf]	[s2]	12ad3b5bbbf407f8e54ea692c07633d1a867c566
lfw_a	LFW-a	Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics	Effective Unconstrained Face Recognition by Combining Multiple Descriptors and Learned Background Statistics	[pdf]	[s2]	133f01aec1534604d184d56de866a4bd531dac87
eth_andreas_ess	ETHZ Pedestrian	Depth and Appearance for Mobile Scene Analysis	Depth and Appearance for Mobile Scene Analysis	[pdf]	[s2]	13f06b08f371ba8b5d31c3e288b4deb61335b462
ijb_c	IJB-A	Pushing the Frontiers of Unconstrained Face Detection and Recognition: IARPA Janus Benchmark A	Pushing the frontiers of unconstrained face detection and recognition: IARPA Janus Benchmark A	[pdf]	[s2]	140c95e53c619eac594d70f6369f518adfea12ef
vgg_faces	VGG Face	Deep Face Recognition	Deep Face Recognition	[pdf]	[s2]	162ea969d1929ed180cc6de9f0bf116993ff6e06
prid	PRID	Person Re-Identification by Descriptive and Discriminative Classification	Person Re-identification by Descriptive and Discriminative Classification	[pdf]	[s2]	16c7c31a7553d99f1837fc6e88e77b5ccbb346b8
umb	UMB	UMB-DB: A Database of Partially Occluded 3D Faces	UMB-DB: A database of partially occluded 3D faces	[pdf]	[s2]	16e8b0a1e8451d5f697b94c0c2b32a00abee1d52
deep_fashion	DeepFashion	DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations	DeepFashion: Powering Robust Clothes Recognition and Retrieval with Rich Annotations	[pdf]	[s2]	18010284894ed0edcca74e5bf768ee2e15ef7841
pilot_parliament	PPB	Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification	Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classification	[pdf]	[s2]	18858cc936947fc96b5c06bbe3c6c2faa5614540
frgc	FRGC	Overview of the Face Recognition Grand Challenge	Overview of the face recognition grand challenge	[pdf]	[s2]	18ae7c9a4bbc832b8b14bc4122070d7939f5e00e
yale_faces	YaleFaces	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	[pdf]	[s2]	18c72175ddbb7d5956d180b65a96005c100f6014
york_3d	UOY 3D Face Database	Three-Dimensional Face Recognition: An Eigensurface Approach	Three-dimensional face recognition: an eigensurface approach	[pdf]	[s2]	19d1b811df60f86cbd5e04a094b07f32fff7a32a
jpl_pose	JPL-Interaction dataset	First-Person Activity Recognition: What Are They Doing to Me?	First-Person Activity Recognition: What Are They Doing to Me?	[pdf]	[s2]	1aad2da473888cb7ebc1bfaa15bfa0f1502ce005
adience	Adience	Age and Gender Estimation of Unfiltered Faces	Age and Gender Estimation of Unfiltered Faces	[pdf]	[s2]	1be498d4bbc30c3bfd0029114c784bc2114d67c0
youtube_poses	YouTube Pose	Personalizing Human Video Pose Estimation	Personalizing Human Video Pose Estimation	[pdf]	[s2]	1c2802c2199b6d15ecefe7ba0c39bfe44363de38
caltech_pedestrians	Caltech Pedestrians	Pedestrian Detection: A Benchmark	Pedestrian detection: A benchmark	[pdf]	[s2]	1dc35905a1deff8bc74688f2d7e2f48fd2273275
immediacy	Immediacy	Multi-task Recurrent Neural Network for Immediacy Prediction	Multi-task Recurrent Neural Network for Immediacy Prediction	[pdf]	[s2]	1e3df3ca8feab0b36fd293fe689f93bb2aaac591
cafe	CAFE	The Child Affective Facial Expression (CAFE) Set: Validity and reliability from untrained adults	The Child Affective Facial Expression (CAFE) set: validity and reliability from untrained adults	[pdf]	[s2]	20388099cc415c772926e47bcbbe554e133343d1
bbc_pose	BBC Pose	Automatic and Efficient Human Pose Estimation for Sign Language Videos	Automatic and Efficient Human Pose Estimation for Sign Language Videos	[pdf]	[s2]	213a579af9e4f57f071b884aa872651372b661fd
3d_rma	3D-RMA	Automatic 3D Face Authentication	Automatic 3D face authentication	[pdf]	[s2]	2160788824c4c29ffe213b2cbeb3f52972d73f37
large_scale_person_search	Large Scale Person Search	End-to-End Deep Learning for Person Search	End-to-End Deep Learning for Person Search	[pdf]	[s2]	2161f6b7ee3c0acc81603b01dc0df689683577b9
images_of_groups	Images of Groups	Understanding Groups of Images of People	Understanding images of groups of people	[pdf]	[s2]	21d9d0deed16f0ad62a4865e9acf0686f4f15492
rap_pedestrian	RAP	A Richly Annotated Dataset for Pedestrian Attribute Recognition	A Richly Annotated Dataset for Pedestrian Attribute Recognition	[pdf]	[s2]	221c18238b829c12b911706947ab38fd017acef7
mot	MOT	Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics	Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics	[pdf]	[s2]	2258e01865367018ed6f4262c880df85b94959f8
saivt	SAIVT SoftBio	A Database for Person Re-Identification in Multi-Camera Surveillance Networks	A Database for Person Re-Identification in Multi-Camera Surveillance Networks	[pdf]	[s2]	22646e00a7ba34d1b5fbe3b1efcd91a1e1be3c2b
pets	PETS 2017	PETS 2017: Dataset and Challenge	PETS 2017: Dataset and Challenge	[pdf]	[s2]	22909dd19a0ec3b6065334cb5be5392cb24d839d
gallagher	Gallagher	Clothing Cosegmentation for Recognizing People	Clothing cosegmentation for recognizing people	[pdf]	[s2]	22ad2c8c0f4d6aa4328b38d894b814ec22579761
expw	ExpW	From Facial Expression Recognition to Interpersonal Relation Prediction	From Facial Expression Recognition to Interpersonal Relation Prediction	[pdf]	[s2]	22f656d0f8426c84a33a267977f511f127bfd7f3
cas_peal	CAS-PEAL	The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations	The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations	[pdf]	[s2]	2485c98aa44131d1a2f7d1355b1e372f2bb148ad
faceplace	Face Place	Recognizing disguised faces	Recognizing disguised faces	[pdf]	[s2]	25474c21613607f6bb7687a281d5f9d4ffa1f9f3
afew_va	AFEW-VA	AFEW-VA database for valence and arousal estimation in-the-wild	AFEW-VA database for valence and arousal estimation in-the-wild	[pdf]	[s2]	2624d84503bc2f8e190e061c5480b6aa4d89277a
cofw	COFW	Robust face landmark estimation under occlusion	Robust Face Landmark Estimation under Occlusion	[pdf]	[s2]	2724ba85ec4a66de18da33925e537f3902f21249
duke_mtmc	Duke MTMC	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	[pdf]	[s2]	27a2fad58dd8727e280f97036e0d2bc55ef5424c
mot	MOT	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking	[pdf]	[s2]	27a2fad58dd8727e280f97036e0d2bc55ef5424c
h3d	H3D	Poselets: Body Part Detectors Trained Using 3D Human Pose Annotations	Poselets: Body part detectors trained using 3D human pose annotations	[pdf]	[s2]	2830fb5282de23d7784b4b4bc37065d27839a412
megaface	MegaFace	Level Playing Field for Million Scale Face Recognition	Level Playing Field for Million Scale Face Recognition	[pdf]	[s2]	28d4e027c7e90b51b7d8908fce68128d1964668a
msceleb	MsCeleb	MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition	MS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition	[pdf]	[s2]	291265db88023e92bb8c8e6390438e5da148e8f5
ferplus	FER+	Training Deep Networks for Facial Expression Recognition with Crowd-Sourced Label Distribution	Training deep networks for facial expression recognition with crowd-sourced label distribution	[pdf]	[s2]	298cbc3dfbbb3a20af4eed97906650a4ea1c29e0
scface	SCface	SCface – surveillance cameras face database	SCface – surveillance cameras face database	[pdf]	[s2]	29a705a5fa76641e0d8963f1fdd67ee4c0d92d3d
peta	PETA	Pedestrian Attribute Recognition At Far Distance	Pedestrian Attribute Recognition At Far Distance	[pdf]	[s2]	2a4bbee0b4cf52d5aadbbc662164f7efba89566c
mmi_facial_expression	MMI Facial Expression Dataset	WEB-BASED DATABASE FOR FACIAL EXPRESSION ANALYSIS	Web-based database for facial expression analysis	[pdf]	[s2]	2a75f34663a60ab1b04a0049ed1d14335129e908
bosphorus	The Bosphorus	Bosphorus Database for 3D Face Analysis	Bosphorus Database for 3D Face Analysis	[pdf]	[s2]	2acf7e58f0a526b957be2099c10aab693f795973
yale_faces	YaleFaces	Acquiring Linear Subspaces for Face Recognition under Variable Lighting	Acquiring linear subspaces for face recognition under variable lighting	[pdf]	[s2]	2ad0ee93d029e790ebb50574f403a09854b65b7e
frav3d	FRAV3D	MULTIMODAL 2D, 2.5D & 3D FACE VERIFICATION	Multimodal 2D, 2.5D & 3D Face Verification	[pdf]	[s2]	2b926b3586399d028b46315d7d9fb9d879e4f79c
clothing_co_parsing	CCP	Clothing Co-Parsing by Joint Image Segmentation and Labeling	Clothing Co-parsing by Joint Image Segmentation and Labeling	[pdf]	[s2]	2bf8541199728262f78d4dced6fb91479b39b738
texas_3dfrd	Texas 3DFRD	Anthropometric 3D Face Recognition	Anthropometric 3D Face Recognition	[pdf]	[s2]	2ce2560cf59db59ce313bbeb004e8ce55c5ce928
a_pascal_yahoo	aPascal	Describing Objects by their Attributes	Describing objects by their attributes	[pdf]	[s2]	2e384f057211426ac5922f1b33d2aa8df5d51f57
3dpes	3DPeS	3DPes: 3D People Dataset for Surveillance and Forensics	3DPeS: 3D people dataset for surveillance and forensics	[pdf]	[s2]	2e8d0f1802e50cccfd3c0aabac0d0beab3a7846e
qmul_grid	GRID	Time-delayed correlation analysis for multi-camera activity understanding	Time-Delayed Correlation Analysis for Multi-Camera Activity Understanding	[pdf]	[s2]	2edb87494278ad11641b6cf7a3f8996de12b8e14
graz	Graz Pedestrian	Generic Object Recognition with Boosting	Generic object recognition with boosting	[pdf]	[s2]	2eed184680edcdec8a3b605ad1a3ba8e8f7cc2e9
names_and_faces_news	News Dataset	Names and Faces	Names and faces in the news	[pdf]	[s2]	2fda164863a06a92d3a910b96eef927269aeb730
umd_faces	UMD	UMDFaces: An Annotated Face Dataset for Training Deep Networks	UMDFaces: An annotated face dataset for training deep networks	[pdf]	[s2]	31b05f65405534a696a847dd19c621b7b8588263
tiny_images	Tiny Images	80 million tiny images: a large dataset for non-parametric object and scene recognition	80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition	[pdf]	[s2]	31b58ced31f22eab10bd3ee2d9174e7c14c27c01
feret	FERET	FERET ( Face Recognition Technology ) Recognition Algorithm Development and Test Results	FERET ( Face Recognition Technology ) Recognition Algorithm Development and Test Results	[pdf]	[s2]	31de9b3dd6106ce6eec9a35991b2b9083395fd0b
ucf_crowd	UCF-CC-50	Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images	Multi-source Multi-scale Counting in Extremely Dense Crowd Images	[pdf]	[s2]	32c801cb7fbeb742edfd94cccfca4934baec71da
cityscapes	Cityscapes	The Cityscapes Dataset for Semantic Urban Scene Understanding	The Cityscapes Dataset for Semantic Urban Scene Understanding	[pdf]	[s2]	32cde90437ab5a70cf003ea36f66f2de0e24b3ab
tud_campus	TUD-Campus	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]	3316521a5527c7700af8ae6aef32a79a8b83672c
tud_crossing	TUD-Crossing	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]	3316521a5527c7700af8ae6aef32a79a8b83672c
tud_pedestrian	TUD-Pedestrian	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]	3316521a5527c7700af8ae6aef32a79a8b83672c
mpii_human_pose	MPII Human Pose	2D Human Pose Estimation: New Benchmark and State of the Art Analysis	2D Human Pose Estimation: New Benchmark and State of the Art Analysis	[pdf]	[s2]	3325860c0c82a93b2eac654f5324dd6a776f609e
penn_fudan	Penn Fudan	Object Detection Combining Recognition and Segmentation	Object Detection Combining Recognition and Segmentation	[pdf]	[s2]	3394168ff0719b03ff65bcea35336a76b21fe5e4
coco_qa	COCO QA	Exploring Models and Data for Image Question Answering	Exploring Models and Data for Image Question Answering	[pdf]	[s2]	35b0331dfcd2897abd5749b49ff5e2b8ba0f7a62
lfw	LFW	Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments	Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments	[pdf]	[s2]	370b5757a5379b15e30d619e4d3fb9e8e13f3256
rafd	RaFD	Presentation and validation of the Radboud Faces Database	Presentation and validation of the Radboud Faces Database	[pdf]	[s2]	3765df816dc5a061bc261e190acc8bdd9d47bec0
vmu	VMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]	37d6f0eb074d207b53885bd2eb78ccc8a04be597
youtube_makeup	YMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]	37d6f0eb074d207b53885bd2eb78ccc8a04be597
cuhk02	CUHK02	Locally Aligned Feature Transforms across Views	Locally Aligned Feature Transforms across Views	[pdf]	[s2]	38b55d95189c5e69cf4ab45098a48fba407609b4
sdu_vid	SDU-VID	A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification	A Spatio-Temporal Appearance Representation for Video-Based Pedestrian Re-Identification	[pdf]	[s2]	3b4ec8af470948a72a6ed37a9fd226719a874ebc
qmul_grid	GRID	Multi-Camera Activity Correlation Analysis	Multi-camera activity correlation analysis	[pdf]	[s2]	3b5b6d19d4733ab606c39c69a889f9e67967f151
tvhi	TVHI	High Five: Recognising human interactions in TV shows	High Five: Recognising human interactions in TV shows	[pdf]	[s2]	3cd40bfa1ff193a96bde0207e5140a399476466c
georgia_tech_face_database	Georgia Tech Face	Maximum likelihood training of the embedded HMM for face detection and recognition	MAXIMUM LIKELIHOOD TRAINING OF THE EMBEDDED HMM FOR FACE DETECTION AND RECOGNITION Ara V. Ne an and Monson H. Hayes III Center for Signal and Image Processing School of Electrical and Computer Engineering	[pdf]	[s2]	3dc3f0b64ef80f573e3a5f96e456e52ee980b877
bio_id	BioID Face	Robust Face Detection Using the Hausdorff Distance	Robust Face Detection Using the Hausdorff Distance	[pdf]	[s2]	4053e3423fb70ad9140ca89351df49675197196a
distance_nighttime	Long Distance Heterogeneous Face	Nighttime Face Recognition at Long Distance: Cross-distance and Cross-spectral Matching	Nighttime Face Recognition at Long Distance: Cross-Distance and Cross-Spectral Matching	[pdf]	[s2]	4156b7e88f2e0ab0a7c095b9bab199ae2b23bd06
market_1501	Market 1501	Scalable Person Re-identification: A Benchmark	Scalable Person Re-identification: A Benchmark	[pdf]	[s2]	4308bd8c28e37e2ed9a3fcfe74d5436cce34b410
tud_multiview	TUD-Multiview	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]	436f798d1a4e54e5947c1e7d7375c31b2bdb4064
tud_stadtmitte	TUD-Stadtmitte	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]	436f798d1a4e54e5947c1e7d7375c31b2bdb4064
cuhk01	CUHK01	Human Reidentification with Transferred Metric Learning	Human Reidentification with Transferred Metric Learning	[pdf]	[s2]	44484d2866f222bbb9b6b0870890f9eea1ffb2d0
vadana	VADANA	VADANA: A dense dataset for facial image analysis	VADANA: A dense dataset for facial image analysis	[pdf]	[s2]	4563b46d42079242f06567b3f2e2f7a80cb3befe
sdu_vid	SDU-VID	Local descriptors encoded by Fisher vectors for person re-identification	Local Descriptors Encoded by Fisher Vectors for Person Re-identification	[pdf]	[s2]	46a01565e6afe7c074affb752e7069ee3bf2e4ef
fia	CMU FiA	The CMU Face In Action (FIA) Database	The CMU Face In Action (FIA) Database	[pdf]	[s2]	47662d1a368daf70ba70ef2d59eb6209f98b675d
kin_face	UB KinFace	Kinship Verification through Transfer Learning	Kinship Verification through Transfer Learning	[pdf]	[s2]	4793f11fbca4a7dba898b9fff68f70d868e2497c
am_fed	AM-FED	Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”	Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"	[pdf]	[s2]	47aeb3b82f54b5ae8142b4bdda7b614433e69b9a
apis	APiS1.0	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	[pdf]	[s2]	488e475eeb3bb39a145f23ede197cd3620f1d98a
svs	SVS	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	[pdf]	[s2]	488e475eeb3bb39a145f23ede197cd3620f1d98a
coco_action	COCO-a	Describing Common Human Visual Actions in Images	Describing Common Human Visual Actions in Images	[pdf]	[s2]	4946ba10a4d5a7d0a38372f23e6622bd347ae273
leeds_sports_pose	Leeds Sports Pose	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	[pdf]	[s2]	4b1d23d17476fcf78f4cbadf69fb130b1aa627c0
stickmen_buffy	Buffy Stickmen	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	[pdf]	[s2]	4b1d23d17476fcf78f4cbadf69fb130b1aa627c0
czech_news_agency	UFI	Unconstrained Facial Images: Database for Face Recognition under Real-world Conditions	Unconstrained Facial Images: Database for Face Recognition Under Real-World Conditions	[pdf]	[s2]	4b4106614c1d553365bad75d7866bff0de6056ed
cmu_pie	CMU PIE	The CMU Pose, Illumination, and Expression Database	The CMU Pose, Illumination, and Expression (PIE) Database	[pdf]	[s2]	4d423acc78273b75134e2afd1777ba6d3a398973
multi_pie	MULTIPIE	Multi-PIE	The CMU Pose, Illumination, and Expression (PIE) Database	[pdf]	[s2]	4d423acc78273b75134e2afd1777ba6d3a398973
3dddb_unconstrained	3D Dynamic	A 3D Dynamic Database for Unconstrained Face Recognition	A 3 D Dynamic Database for Unconstrained Face Recognition	[pdf]	[s2]	4d4bb462c9f1d4e4ab1e4aa6a75cc0bc71b38461
texas_3dfrd	Texas 3DFRD	Texas 3D Face Recognition Database	Texas 3D Face Recognition Database	[pdf]	[s2]	4d58f886f5150b2d5e48fd1b5a49e09799bf895d
cohn_kanade_plus	CK+	The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression	The Extended Cohn-Kanade Dataset (CK+): A complete dataset for action unit and emotion-specified expression	[pdf]	[s2]	4d9a02d080636e9666c4d1cc438b9893391ec6c7
cfd	CFD	The Chicago face database: A free stimulus set of faces and norming data	The Chicago face database: A free stimulus set of faces and norming data.	[pdf]	[s2]	4df3143922bcdf7db78eb91e6b5359d6ada004d2
leeds_sports_pose_extended	Leeds Sports Pose Extended	Learning Effective Human Pose Estimation from Inaccurate Annotation	Learning effective human pose estimation from inaccurate annotation	[pdf]	[s2]	4e4746094bf60ee83e40d8597a6191e463b57f76
dartmouth_children	Dartmouth Children	The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set	The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set	[pdf]	[s2]	4e6ee936eb50dd032f7138702fa39b7c18ee8907
soton	SOTON HiD	On a Large Sequence-Based Human Gait Database	On a large sequence-based human gait database	[pdf]	[s2]	4f93cd09785c6e77bf4bc5a788e079df524c8d21
violent_flows	Violent Flows	Violent Flows: Real-Time Detection of Violent Crowd Behavior	Violent flows: Real-time detection of violent crowd behavior	[pdf]	[s2]	5194cbd51f9769ab25260446b4fa17204752e799
bp4d_plus	BP4D+	Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis	Multimodal Spontaneous Emotion Corpus for Human Behavior Analysis	[pdf]	[s2]	53ae38a6bb2b21b42bac4f0c4c8ed1f9fa02f9d4
reseed	ReSEED	ReSEED: Social Event dEtection Dataset	ReSEED: social event dEtection dataset	[pdf]	[s2]	54983972aafc8e149259d913524581357b0f91c3
orl	ORL	Parameterisation of a Stochastic Model for Human Face Identification	Parameterisation of a stochastic model for human face identification	[pdf]	[s2]	55206f0b5f57ce17358999145506cd01e570358c
ifad	IFAD	Indian Face Age Database: A Database for Face Recognition with Age Variation	Indian Face Age Database : A Database for Face Recognition with Age Variation	[pdf]	[s2]	55c40cbcf49a0225e72d911d762c27bb1c2d14aa
data_61	Data61 Pedestrian	A Multi-Modal Graphical Model for Scene Analysis	A Multi-modal Graphical Model for Scene Analysis	[pdf]	[s2]	563c940054e4b456661762c1ab858e6f730c3159
unbc_shoulder_pain	UNBC-McMaster Pain	PAINFUL DATA: The UNBC-McMaster Shoulder Pain Expression Archive Database	Painful data: The UNBC-McMaster shoulder pain expression archive database	[pdf]	[s2]	56ffa7d906b08d02d6d5a12c7377a57e24ef3391
stanford_drone	Stanford Drone	Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes	Social LSTM: Human Trajectory Prediction in Crowded Spaces	[pdf]	[s2]	570f37ed63142312e6ccdf00ecc376341ec72b9f
ijb_c	IJB-C	IARPA Janus Benchmark C	IARPA Janus Benchmark - C: Face Dataset and Protocol	[pdf]	[s2]	57178b36c21fd7f4529ac6748614bb3374714e91
50_people_one_question	50 People One Question	Merging Pose Estimates Across Space and Time	Merging Pose Estimates Across Space and Time	[pdf]	[s2]	5753b2b5e442eaa3be066daa4a2ca8d8a0bb1725
mr2	MR2	The MR2: A multi-racial mega-resolution database of facial stimuli	The MR2: A multi-racial, mega-resolution database of facial stimuli.	[pdf]	[s2]	578d4ad74818086bb64f182f72e2c8bd31e3d426
cvc_01_barcelona	CVC-01	Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection	Adaptive Image Sampling and Windows Classification for On – board Pedestrian Detection	[pdf]	[s2]	57fe081950f21ca03b5b375ae3e84b399c015861
mot	MOT	Learning to associate: HybridBoosted multi-target tracker for crowded scene	Learning to associate: HybridBoosted multi-target tracker for crowded scene	[pdf]	[s2]	5981e6479c3fd4e31644db35d236bfb84ae46514
disfa	DISFA	DISFA: A Spontaneous Facial Action Intensity Database	DISFA: A Spontaneous Facial Action Intensity Database	[pdf]	[s2]	5a5f0287484f0d480fed1ce585dbf729586f0edc
wlfdb	WLFDB	WLFDB: Weakly Labeled Face Databases	WLFDB: Weakly Labeled Face Databases	[pdf]	[s2]	5ad4e9f947c1653c247d418f05dad758a3f9277b
coco	COCO	Microsoft COCO: Common Objects in Context	Microsoft COCO: Common Objects in Context	[pdf]	[s2]	5e0f8c355a37a5a89351c02f174e7a5ddcb98683
cityscapes	Cityscapes	The Cityscapes Dataset	The Cityscapes Dataset	[pdf]	[s2]	5ffd74d2873b7cba2cbc5fd295cc7fbdedca22a2
viper	VIPeR	Evaluating Appearance Models for Recognition, Reacquisition, and Tracking	Evaluating Appearance Models for Recognition , Reacquisition , and Tracking	[pdf]	[s2]	6273b3491e94ea4dd1ce42b791d77bdc96ee73a8
caltech_10k_web_faces	Caltech 10K Web Faces	Pruning Training Sets for Learning of Object Categories	Pruning training sets for learning of object categories	[pdf]	[s2]	636b8ffc09b1b23ff714ac8350bb35635e49fa3c
bfm	BFM	A 3D Face Model for Pose and Illumination Invariant Face Recognition	A 3D Face Model for Pose and Illumination Invariant Face Recognition	[pdf]	[s2]	639937b3a1b8bded3f7e9a40e85bd3770016cf3c
alert_airport	ALERT Airport	A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets	A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.	[pdf]	[s2]	6403117f9c005ae81f1e8e6d1302f4a045e3d99d
complex_activities	Ongoing Complex Activities	Recognition of Ongoing Complex Activities by Sequence Prediction over a Hierarchical Label Space	Recognition of ongoing complex activities by sequence prediction over a hierarchical label space	[pdf]	[s2]	65355cbb581a219bd7461d48b3afd115263ea760
afad	AFAD	Ordinal Regression with a Multiple Output CNN for Age Estimation	Ordinal Regression with Multiple Output CNN for Age Estimation	[pdf]	[s2]	6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c
sun_attributes	SUN	The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding	The SUN Attribute Database: Beyond Categories for Deeper Scene Understanding	[pdf]	[s2]	66e6f08873325d37e0ec20a4769ce881e04e964e
tud_brussels	TUD-Brussels	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]	6ad5a38df8dd4cdddd74f31996ce096d41219f72
tud_motionpairs	TUD-Motionparis	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]	6ad5a38df8dd4cdddd74f31996ce096d41219f72
cuhk03	CUHK03	DeepReID: Deep Filter Pairing Neural Network for Person Re-identification	DeepReID: Deep Filter Pairing Neural Network for Person Re-identification	[pdf]	[s2]	6bd36e9fd0ef20a3074e1430a6cc601e6d407fc3
ar_facedb	AR Face	The AR Face Database	The AR face database	[pdf]	[s2]	6d96f946aaabc734af7fe3fc4454cf8547fcd5ed
agedb	AgeDB	AgeDB: the first manually collected, in-the-wild age database	AgeDB: The First Manually Collected, In-the-Wild Age Database	[pdf]	[s2]	6dcf418c778f528b5792104760f1fbfe90c6dd6a
stickmen_buffy	Buffy Stickmen	Learning to Parse Images of Articulated Objects	Learning to parse images of articulated bodies	[pdf]	[s2]	6dd0597f8513dc100cd0bc1b493768cde45098a9
stickmen_pascal	Stickmen PASCAL	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Learning to parse images of articulated bodies	[pdf]	[s2]	6dd0597f8513dc100cd0bc1b493768cde45098a9
stickmen_pascal	Stickmen PASCAL	Learning to Parse Images of Articulated Objects	Learning to parse images of articulated bodies	[pdf]	[s2]	6dd0597f8513dc100cd0bc1b493768cde45098a9
ward	WARD	Re-identify people in wide area camera network	Re-identify people in wide area camera network	[pdf]	[s2]	6f3c76b7c0bd8e1d122c6ea808a271fd4749c951
umd_faces	UMD	The Do's and Don'ts for CNN-based Face Verification	The Do’s and Don’ts for CNN-Based Face Verification	[pdf]	[s2]	71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6
affectnet	AffectNet	AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild	AffectNet: A Database for Facial Expression, Valence, and Arousal Computing in the Wild	[pdf]	[s2]	758d7e1be64cc668c59ef33ba8882c8597406e53
wildtrack	WildTrack	WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	[pdf]	[s2]	77c81c13a110a341c140995bedb98101b9e84f7f
berkeley_pose	BPAD	Describing People: A Poselet-Based Approach to Attribute Classification	Describing people: A poselet-based approach to attribute classification	[pdf]	[s2]	7808937b46acad36e43c30ae4e9f3fd57462853d
mapillary	Mapillary	The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes	The Mapillary Vistas Dataset for Semantic Understanding of Street Scenes	[pdf]	[s2]	79828e6e9f137a583082b8b5a9dfce0c301989b8
nudedetection	Nude Detection	A Bag-of-Features Approach based on Hue-SIFT Descriptor for Nude Detection	A bag-of-features approach based on Hue-SIFT descriptor for nude detection	[pdf]	[s2]	7ace44190729927e5cb0dd5d363fcae966fe13f7
lfw	LFW	Labeled Faces in the Wild: A Survey	Labeled Faces in the Wild : A Survey	[pdf]	[s2]	7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22
nova_emotions	Novaemötions Dataset	Competitive affective gamming: Winning with a smile	Competitive affective gaming: winning with a smile	[pdf]	[s2]	7f4040b482d16354d5938c1d1b926b544652bf5b
sun_attributes	SUN	SUN Attribute Database: Discovering, Annotating, and Recognizing Scene Attributes	SUN attribute database: Discovering, annotating, and recognizing scene attributes	[pdf]	[s2]	833fa04463d90aab4a9fe2870d480f0b40df446e
svs	SVS	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	Pedestrian Attribute Classification in Surveillance: Database and Evaluation	[pdf]	[s2]	488e475eeb3bb39a145f23ede197cd3620f1d98a
texas_3dfrd	Texas 3DFRD	Texas 3D Face Recognition Database	Texas 3D Face Recognition Database	[pdf]	[s2]	4d58f886f5150b2d5e48fd1b5a49e09799bf895d
texas_3dfrd	Texas 3DFRD	Anthropometric 3D Face Recognition	Anthropometric 3D Face Recognition	[pdf]	[s2]	2ce2560cf59db59ce313bbeb004e8ce55c5ce928
tiny_faces	TinyFace	Low-Resolution Face Recognition	Low-Resolution Face Recognition	[pdf]	[s2]	8990cdce3f917dad622e43e033db686b354d057c
tiny_images	Tiny Images	80 million tiny images: a large dataset for non-parametric object and scene recognition	80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition	[pdf]	[s2]	31b58ced31f22eab10bd3ee2d9174e7c14c27c01
towncenter	TownCenter	Stable Multi-Target Tracking in Real-Time Surveillance Video	Stable multi-target tracking in real-time surveillance video	[pdf]	[s2]	9361b784e73e9238d5cefbea5ac40d35d1e3103f
tud_brussels	TUD-Brussels	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]	6ad5a38df8dd4cdddd74f31996ce096d41219f72
tud_campus	TUD-Campus	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]	3316521a5527c7700af8ae6aef32a79a8b83672c
tud_crossing	TUD-Crossing	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]	3316521a5527c7700af8ae6aef32a79a8b83672c
tud_motionpairs	TUD-Motionparis	Multi-Cue Onboard Pedestrian Detection	Multi-cue onboard pedestrian detection	[pdf]	[s2]	6ad5a38df8dd4cdddd74f31996ce096d41219f72
tud_multiview	TUD-Multiview	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]	436f798d1a4e54e5947c1e7d7375c31b2bdb4064
tud_pedestrian	TUD-Pedestrian	People-Tracking-by-Detection and People-Detection-by-Tracking	People-tracking-by-detection and people-detection-by-tracking	[pdf]	[s2]	3316521a5527c7700af8ae6aef32a79a8b83672c
tud_stadtmitte	TUD-Stadtmitte	Monocular 3D Pose Estimation and Tracking by Detection	Monocular 3D pose estimation and tracking by detection	[pdf]	[s2]	436f798d1a4e54e5947c1e7d7375c31b2bdb4064
tvhi	TVHI	High Five: Recognising human interactions in TV shows	High Five: Recognising human interactions in TV shows	[pdf]	[s2]	3cd40bfa1ff193a96bde0207e5140a399476466c
ucf_crowd	UCF-CC-50	Multi-Source Multi-Scale Counting in Extremely Dense Crowd Images	Multi-source Multi-scale Counting in Extremely Dense Crowd Images	[pdf]	[s2]	32c801cb7fbeb742edfd94cccfca4934baec71da
ucf_selfie	UCF Selfie	How to Take a Good Selfie?	How to Take a Good Selfie?	[pdf]	[s2]	041d3eedf5e45ce5c5229f0181c5c576ed1fafd6
umb	UMB	UMB-DB: A Database of Partially Occluded 3D Faces	UMB-DB: A database of partially occluded 3D faces	[pdf]	[s2]	16e8b0a1e8451d5f697b94c0c2b32a00abee1d52
umd_faces	UMD	UMDFaces: An Annotated Face Dataset for Training Deep Networks	UMDFaces: An annotated face dataset for training deep networks	[pdf]	[s2]	31b05f65405534a696a847dd19c621b7b8588263
umd_faces	UMD	The Do's and Don'ts for CNN-based Face Verification	The Do’s and Don’ts for CNN-Based Face Verification	[pdf]	[s2]	71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6
unbc_shoulder_pain	UNBC-McMaster Pain	PAINFUL DATA: The UNBC-McMaster Shoulder Pain Expression Archive Database	Painful data: The UNBC-McMaster shoulder pain expression archive database	[pdf]	[s2]	56ffa7d906b08d02d6d5a12c7377a57e24ef3391
used	USED Social Event Dataset	USED: A Large-scale Social Event Detection Dataset	USED: a large-scale social event detection dataset	[pdf]	[s2]	8627f019882b024aef92e4eb9355c499c733e5b7
v47	V47	Re-identification of Pedestrians with Variable Occlusion and Scale	Re-identification of pedestrians with variable occlusion and scale	[pdf]	[s2]	922e0a51a3b8c67c4c6ac09a577ff674cbd28b34
vadana	VADANA	VADANA: A dense dataset for facial image analysis	VADANA: A dense dataset for facial image analysis	[pdf]	[s2]	4563b46d42079242f06567b3f2e2f7a80cb3befe
vgg_faces	VGG Face	Deep Face Recognition	Deep Face Recognition	[pdf]	[s2]	162ea969d1929ed180cc6de9f0bf116993ff6e06
violent_flows	Violent Flows	Violent Flows: Real-Time Detection of Violent Crowd Behavior	Violent flows: Real-time detection of violent crowd behavior	[pdf]	[s2]	5194cbd51f9769ab25260446b4fa17204752e799
viper	VIPeR	Evaluating Appearance Models for Recognition, Reacquisition, and Tracking	Evaluating Appearance Models for Recognition , Reacquisition , and Tracking	[pdf]	[s2]	6273b3491e94ea4dd1ce42b791d77bdc96ee73a8
visual_phrases	Phrasal Recognition	Recognition using Visual Phrases	Recognition using visual phrases	[pdf]	[s2]	e8de844fefd54541b71c9823416daa238be65546
vmu	VMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]	37d6f0eb074d207b53885bd2eb78ccc8a04be597
voc	VOC	The PASCAL Visual Object Classes (VOC) Challenge	The Pascal Visual Object Classes (VOC) Challenge	[pdf]	[s2]	0ee1916a0cb2dc7d3add086b5f1092c3d4beb38a
vqa	VQA	VQA: Visual Question Answering	VQA: Visual Question Answering	[pdf]	[s2]	01959ef569f74c286956024866c1d107099199f7
ward	WARD	Re-identify people in wide area camera network	Re-identify people in wide area camera network	[pdf]	[s2]	6f3c76b7c0bd8e1d122c6ea808a271fd4749c951
who_goes_there	WGT	Who Goes There? Approaches to Mapping Facial Appearance Diversity	Who goes there?: approaches to mapping facial appearance diversity	[pdf]	[s2]	9b9bf5e623cb8af7407d2d2d857bc3f1b531c182
wildtrack	WildTrack	WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	[pdf]	[s2]	77c81c13a110a341c140995bedb98101b9e84f7f
wlfdb		WLFDB: Weakly Labeled Face Databases	WLFDB: Weakly Labeled Face Databases	[pdf]	[s2]	5ad4e9f947c1653c247d418f05dad758a3f9277b
yale_faces	YaleFaces	Acquiring Linear Subspaces for Face Recognition under Variable Lighting	Acquiring linear subspaces for face recognition under variable lighting	[pdf]	[s2]	2ad0ee93d029e790ebb50574f403a09854b65b7e
yale_faces	YaleFaces	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	From Few to Many: Illumination Cone Models for Face Recognition under Variable Lighting and Pose	[pdf]	[s2]	18c72175ddbb7d5956d180b65a96005c100f6014
yawdd	YawDD	YawDD: A Yawning Detection Dataset	YawDD: a yawning detection dataset	[pdf]	[s2]	a94cae786d515d3450d48267e12ca954aab791c4
yfcc_100m	YFCC100M	YFCC100M: The New Data in Multimedia Research	YFCC100M: the new data in multimedia research	[pdf]	[s2]	010f0f4929e6a6644fb01f0e43820f91d0fad292
york_3d	UOY 3D Face Database	Three-Dimensional Face Recognition: An Eigensurface Approach	Three-dimensional face recognition: an eigensurface approach	[pdf]	[s2]	19d1b811df60f86cbd5e04a094b07f32fff7a32a
youtube_makeup	YMU	Can Facial Cosmetics Affect the Matching Accuracy of Face Recognition Systems?	Can facial cosmetics affect the matching accuracy of face recognition systems?	[pdf]	[s2]	37d6f0eb074d207b53885bd2eb78ccc8a04be597
youtube_poses	YouTube Pose	Personalizing Human Video Pose Estimation	Personalizing Human Video Pose Estimation	[pdf]	[s2]	1c2802c2199b6d15ecefe7ba0c39bfe44363de38
gfw	YouTube Pose	Merge or Not? Learning to Group Faces via Imitation Learning	Merge or Not? Learning to Group Faces via Imitation Learning	[pdf]	[s2]	e58dd160a76349d46f881bd6ddbc2921f08d1050

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833fa04463d90aab4a9fe2870d480f0b40df446e

imdb_wiki

IMDB

DEX: Deep EXpectation of apparent age from a single image

DEX: Deep EXpectation of Apparent Age from a Single Image

[pdf]

[s2]

8355d095d3534ef511a9af68a3b2893339e3f96b

awe_ears

AWE Ears

Ear Recognition: More Than a Survey

[pdf]

[s2]

84fe5b4ac805af63206012d29523a1e033bc827e

casia_webface

CASIA Webface

Learning Face Representation from Scratch

[pdf]

[s2]

853bd61bc48a431b9b1c7cab10c603830c488e39

used

USED Social Event Dataset

USED: A Large-scale Social Event Detection Dataset

USED: a large-scale social event detection dataset

[pdf]

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8627f019882b024aef92e4eb9355c499c733e5b7

tiny_faces

TinyFace

Low-Resolution Face Recognition

[pdf]

[s2]

8990cdce3f917dad622e43e033db686b354d057c

10k_US_adult_faces

10K US Adult Faces

The intrinsic memorability of face images

The intrinsic memorability of face photographs.

[pdf]

[s2]

8b2dd5c61b23ead5ae5508bb8ce808b5ea266730

fei

FEI

Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro

A new ranking method for principal components analysis and its application to face image analysis

[pdf]

[s2]

8b56e33f33e582f3e473dba573a16b598ed9bcdc

chalearn

ChaLearn

ChaLearn Looking at People: A Review of Events and Resources

ChaLearn looking at people: A review of events and resources

[pdf]

[s2]

8d5998cd984e7cce307da7d46f155f9db99c6590

hda_plus

HDA+

The HDA+ data set for research on fully automated re-identification systems

The HDA+ Data Set for Research on Fully Automated Re-identification Systems

[pdf]

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8f02ec0be21461fbcedf51d864f944cfc42c875f

morph

MORPH Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

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9055b155cbabdce3b98e16e5ac9c0edf00f9552f

morph_nc

MORPH Non-Commercial

MORPH: A Longitudinal Image Database of Normal Adult Age-Progression

MORPH: a longitudinal image database of normal adult age-progression

[pdf]

[s2]

9055b155cbabdce3b98e16e5ac9c0edf00f9552f

v47

V47

Re-identification of Pedestrians with Variable Occlusion and Scale

Re-identification of pedestrians with variable occlusion and scale

[pdf]

[s2]

922e0a51a3b8c67c4c6ac09a577ff674cbd28b34

towncenter

TownCenter

Stable Multi-Target Tracking in Real-Time Surveillance Video

Stable multi-target tracking in real-time surveillance video

[pdf]

[s2]

9361b784e73e9238d5cefbea5ac40d35d1e3103f

4dfab

4DFAB

4DFAB: A Large Scale 4D Facial Expression Database for Biometric Applications

[pdf]

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9696ad8b164f5e10fcfe23aacf74bd6168aebb15

ilids_vid_reid

iLIDS-VID

Person Re-Identication by Video Ranking

Person Re-identification by Video Ranking

[pdf]

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98bb029afe2a1239c3fdab517323066f0957b81b

sdu_vid

SDU-VID

Person reidentification by video ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

m2vts

The M2VTS Multimodal Face Database (Release 1.00)

[pdf]

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who_goes_there

WGT

Who Goes There? Approaches to Mapping Facial Appearance Diversity

Who goes there?: approaches to mapping facial appearance diversity

[pdf]

[s2]

9b9bf5e623cb8af7407d2d2d857bc3f1b531c182

precarious

Precarious

Expecting the Unexpected: Training Detectors for Unusual Pedestrians With Adversarial Imposters

Expecting the Unexpected: Training Detectors for Unusual Pedestrians with Adversarial Imposters

[pdf]

[s2]

9e5378e7b336c89735d3bb15cf67eff96f86d39a

mafl

MAFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

mtfl

MTFL

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

moments_in_time

Moments in Time

Moments in Time Dataset: one million videos for event understanding

[pdf]

[s2]

a5a44a32a91474f00a3cda671a802e87c899fbb4

aflw

AFLW

Annotated Facial Landmarks in the Wild: A Large-scale, Real-world Database for Facial Landmark Localization

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

market1203

Market 1203

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

pku_reid

PKU-Reid

Orientation driven bag of appearances for person re-identification

Orientation Driven Bag of Appearances for Person Re-identification

[pdf]

[s2]

a7fe834a0af614ce6b50dc093132b031dd9a856b

hi4d_adsip

Hi4D-ADSIP

Hi4D-ADSIP 3-D dynamic facial articulation database

[pdf]

[s2]

a8d0b149c2eadaa02204d3e4356fbc8eccf3b315

yawdd

YawDD

YawDD: A Yawning Detection Dataset

YawDD: a yawning detection dataset

[pdf]

[s2]

a94cae786d515d3450d48267e12ca954aab791c4

mrp_drone

MRP Drone

Investigating Open-World Person Re-identification Using a Drone

[pdf]

[s2]

ad01687649d95cd5b56d7399a9603c4b8e2217d7

put_face

Put Face

The PUT face database

The put face database

[pdf]

[s2]

ae0aee03d946efffdc7af2362a42d3750e7dd48a

m2vtsdb_extended

xm2vtsdb

XM2VTSDB: The Extended M2VTS Database

Xm2vtsdb: the Extended M2vts Database

[pdf]

[s2]

b62628ac06bbac998a3ab825324a41a11bc3a988

ifdb

IFDB

Iranian Face Database with age, pose and expression

[pdf]

[s2]

b71d1aa90dcbe3638888725314c0d56640c1fef1

pornodb

Pornography DB

Pooling in Image Representation: the Visual Codeword Point of View

Pooling in image representation: The visual codeword point of view

[pdf]

[s2]

b92a1ed9622b8268ae3ac9090e25789fc41cc9b8

hda_plus

HDA+

A Multi-camera video data set for research on High-Definition surveillance

HDA dataset-DRAFT 1 A Multi-camera video data set for research on High-Definition surveillance

[pdf]

[s2]

bd88bb2e4f351352d88ee7375af834360e223498

mars

MARS

MARS: A Video Benchmark for Large-Scale Person Re-identification

MARS: A Video Benchmark for Large-Scale Person Re-Identification

[pdf]

[s2]

c0387e788a52f10bf35d4d50659cfa515d89fbec

nova_emotions

Novaemötions Dataset

Crowdsourcing facial expressions for affective-interaction

[pdf]

[s2]

c06b13d0ec3f5c43e2782cd22542588e233733c3

mcgill

McGill Real World

Hierarchical Temporal Graphical Model for Head Pose Estimation and Subsequent Attribute Classification in Real-World Videos

Hierarchical temporal graphical model for head pose estimation and subsequent attribute classification in real-world videos

[pdf]

[s2]

a5a3bc3e5e9753769163cb30b16dbd12e266b93e

qmul_surv_face

QMUL-SurvFace

Surveillance Face Recognition Challenge

[pdf]

[s2]

c866a2afc871910e3282fd9498dce4ab20f6a332

emotio_net

EmotioNet Database

EmotioNet: An Accurate, Real-Time Algorithm for the Automatic Annotation of a Million Facial Expressions in the Wild

[pdf]

[s2]

c900e0ad4c95948baaf0acd8449fde26f9b4952a

imfdb

IMFDB

Indian Movie Face Database: A Benchmark for Face Recognition Under Wide Variations

Indian Movie Face Database: A benchmark for face recognition under wide variations

[pdf]

[s2]

ca3e88d87e1344d076c964ea89d91a75c417f5ee

b3d_ac

B3D(AC)

A 3-D Audio-Visual Corpus of Affective Communication

[pdf]

[s2]

d08cc366a4a0192a01e9a7495af1eb5d9f9e73ae

jiku_mobile

Jiku Mobile Video Dataset

The Jiku Mobile Video Dataset

The jiku mobile video dataset

[pdf]

[s2]

d178cde92ab3dc0dd2ebee5a76a33d556c39448b

stair_actions

STAIR Action

STAIR Actions: A Video Dataset of Everyday Home Actions

[pdf]

[s2]

d3f5a1848b0028d8ab51d0b0673732cad2e3c8c9

feret

FERET

The FERET database and evaluation procedure for face-recognition algorithms

[pdf]

[s2]

dc8b25e35a3acb812beb499844734081722319b4

families_in_the_wild

FIW

Visual Kinship Recognition of Families in the Wild

[pdf]

[s2]

dd65f71dac86e36eecbd3ed225d016c3336b4a13

scut_head

SCUT HEAD

Detecting Heads using Feature Refine Net and Cascaded Multi-scale Architecture

[pdf]

[s2]

d3200d49a19a4a4e4e9745ee39649b65d80c834b

sarc3d

Sarc3D

SARC3D: a new 3D body model for People Tracking and Re-identification

SARC3D: A New 3D Body Model for People Tracking and Re-identification

[pdf]

[s2]

e27ef52c641c2b5100a1b34fd0b819e84a31b4df

fiw_300

300-W

300 faces In-the-wild challenge: Database and results

300 Faces In-The-Wild Challenge: database and results

[pdf]

[s2]

e4754afaa15b1b53e70743880484b8d0736990ff

gfw

YouTube Pose

Merge or Not? Learning to Group Faces via Imitation Learning

[pdf]

[s2]

e58dd160a76349d46f881bd6ddbc2921f08d1050

visual_phrases

Phrasal Recognition

Recognition using Visual Phrases

Recognition using visual phrases

[pdf]

[s2]

e8de844fefd54541b71c9823416daa238be65546

mpi_large

Large MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

mpi_small

Small MPI Facial Expression

The MPI Facial Expression Database — A Validated Database of Emotional and Conversational Facial Expressions

[pdf]

[s2]

ea050801199f98a1c7c1df6769f23f658299a3ae

msmt_17

MSMT17

Person Transfer GAN to Bridge Domain Gap for Person Re-Identification

[pdf]

[s2]

ec792ad2433b6579f2566c932ee414111e194537

europersons

EuroCity Persons

The EuroCity Persons Dataset: A Novel Benchmark for Object Detection

[pdf]

[s2]

f0e17f27f029db4ad650ff278fe3c10ecb6cb0c4

pku

PKU

Swiss-System Based Cascade Ranking for Gait-based Person Re-identification

Swiss-System Based Cascade Ranking for Gait-Based Person Re-Identification

[pdf]

[s2]

f6c8d5e35d7e4d60a0104f233ac1a3ab757da53f

caltech_pedestrians

Caltech Pedestrians

Pedestrian Detection: An Evaluation of the State of the Art

[pdf]

[s2]

f72f6a45ee240cc99296a287ff725aaa7e7ebb35

iit_dehli_ear

IIT Dehli Ear

Automated human identification using ear imaging

Automated Human Identification Using Ear Imaging

[pdf]

[s2]

faf40ce28857aedf183e193486f5b4b0a8c478a2

nd_2006

ND-2006

Using a Multi-Instance Enrollment Representation to Improve 3D Face Recognition

[pdf]

[s2]

fd8168f1c50de85bac58a8d328df0a50248b16ae

\ No newline at end of file diff --git a/scraper/reports/paper_title_report_nonmatching.html b/scraper/reports/paper_title_report_nonmatching.html index 7e6ca73c..d24cec59 100644 --- a/scraper/reports/paper_title_report_nonmatching.html +++ b/scraper/reports/paper_title_report_nonmatching.html @@ -1,3 +1,3 @@ -Paper Titles that do not match

Paper Titles that do not match

key

name

our title

found title

address

s2 id

10k_US_adult_faces

10K US Adult Faces

The intrinsic memorability of face images

The intrinsic memorability of face photographs.

[pdf]

[s2]

8b2dd5c61b23ead5ae5508bb8ce808b5ea266730

3dddb_unconstrained

3D Dynamic

A 3D Dynamic Database for Unconstrained Face Recognition

A 3 D Dynamic Database for Unconstrained Face Recognition

[pdf]

[s2]

4d4bb462c9f1d4e4ab1e4aa6a75cc0bc71b38461

afad

AFAD

Ordinal Regression with a Multiple Output CNN for Age Estimation

Ordinal Regression with Multiple Output CNN for Age Estimation

[pdf]

[s2]

6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c

afw

AFW

Face detection, pose estimation and landmark localization in the wild

Face detection, pose estimation, and landmark localization in the wild

[pdf]

[s2]

University of California, Irvine

0e986f51fe45b00633de9fd0c94d082d2be51406

alert_airport

ALERT Airport

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets

A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.

[pdf]

[s2]

6403117f9c005ae81f1e8e6d1302f4a045e3d99d

am_fed

AM-FED

Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”

Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"

[pdf]

[s2]

47aeb3b82f54b5ae8142b4bdda7b614433e69b9a

bjut_3d

BJUT-3D

The BJUT-3D Large-Scale Chinese Face Database

A novel face recognition method based on 3D face model

[pdf]

[s2]

1ed1a49534ad8dd00f81939449f6389cfbc25321

bp4d_spontanous

BP4D-Spontanous

A high resolution spontaneous 3D dynamic facial expression database

A high-resolution spontaneous 3D dynamic facial expression database

[pdf]

[s2]

SUNY Binghamton

b91f54e1581fbbf60392364323d00a0cd43e493c

brainwash

Brainwash

Brainwash dataset

Brainwash: A Data System for Feature Engineering

[pdf]

[s2]

214c966d1f9c2a4b66f4535d9a0d4078e63a5867

camel

CAMEL

CAMEL Dataset for Visual and Thermal Infrared Multiple Object Detection and Tracking

Application of Object Based Classification and High Resolution Satellite Imagery for Savanna Ecosystem Analysis

[pdf]

[s2]

5801690199c1917fa58c35c3dead177c0b8f9f2d

casablanca

Casablanca

Context-aware {CNNs} for person head detection

Context-Aware CNNs for Person Head Detection

[pdf]

[s2]

0ceda9dae8b9f322df65ca2ef02caca9758aec6f

cfd

CFD

The Chicago face database: A free stimulus set of faces and norming data

The Chicago face database: A free stimulus set of faces and norming data.

[pdf]

[s2]

4df3143922bcdf7db78eb91e6b5359d6ada004d2

cmu_pie

CMU PIE

The CMU Pose, Illumination, and Expression Database

The CMU Pose, Illumination, and Expression (PIE) Database

[pdf]

[s2]

4d423acc78273b75134e2afd1777ba6d3a398973

columbia_gaze

Columbia Gaze

Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction

Gaze locking: passive eye contact detection for human-object interaction

[pdf]

[s2]

06f02199690961ba52997cde1527e714d2b3bf8f

cvc_01_barcelona

CVC-01

Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection

Adaptive Image Sampling and Windows Classification for On – board Pedestrian Detection

[pdf]

[s2]

57fe081950f21ca03b5b375ae3e84b399c015861

d3dfacs

D3DFACS

A FACS Valid 3D Dynamic Action Unit database with Applications to 3D Dynamic Morphable Facial Modelling

A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling

[pdf]

[s2]

Jacobs University

070de852bc6eb275d7ca3a9cdde8f6be8795d1a3

dartmouth_children

Dartmouth Children

The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set

The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set

[pdf]

[s2]

4e6ee936eb50dd032f7138702fa39b7c18ee8907

disfa

DISFA

DISFA: A Spontaneous Facial Action Intensity Database

Extended DISFA Dataset: Investigating Posed and Spontaneous Facial Expressions

[pdf]

[s2]

a5acda0e8c0937bfed013e6382da127103e41395

face_research_lab

Face Research Lab London

Face Research Lab London Set. figshare

Anxiety promotes memory for mood-congruent faces but does not alter loss aversion.

[pdf]

[s2]

University College London

c6526dd3060d63a6c90e8b7ff340383c4e0e0dd8

fddb

FDDB

FDDB: A Benchmark for Face Detection in Unconstrained Settings

A Benchmark for Face Detection in Unconstrained Settings

[pdf]

[s2]

University of Massachusetts

75da1df4ed319926c544eefe17ec8d720feef8c0

fei

FEI

Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro

Generalização cartográfica automatizada para um banco de dados cadastral

[pdf]

[s2]

b6b1b0632eb9d4ab1427278f5e5c46f97753c73d

frgc

FRGC

Overview of the Face Recognition Grand Challenge

Overview of the face recognition grand challenge

[pdf]

[s2]

18ae7c9a4bbc832b8b14bc4122070d7939f5e00e

gavab_db

Gavab

GavabDB: a 3D face database

Expression invariant 3D face recognition with a Morphable Model

[pdf]

[s2]

42505464808dfb446f521fc6ff2cfeffd4d68ff1

georgia_tech_face_database

Georgia Tech Face

Maximum likelihood training of the embedded HMM for face detection and recognition

[pdf]

[s2]

3dc3f0b64ef80f573e3a5f96e456e52ee980b877

hda_plus

HDA+

A Multi-camera video data set for research on High-Definition surveillance

HDA dataset-DRAFT 1 A Multi-camera video data set for research on High-Definition surveillance

[pdf]

[s2]

bd88bb2e4f351352d88ee7375af834360e223498

hi4d_adsip

Hi4D-ADSIP

Hi4D-ADSIP 3-D dynamic facial articulation database

High-resolution comprehensive 3-D dynamic database for facial articulation analysis

[pdf]

[s2]

24830e3979d4ed01b9fd0feebf4a8fd22e0c35fd

hrt_transgender

HRT Transgender

Face recognition across gender transformation using SVM Classifier

Face recognition: A literature survey

[pdf]

[s2]

28312c3a47c1be3a67365700744d3d6665b86f22

ifad

IFAD

Indian Face Age Database: A Database for Face Recognition with Age Variation

Indian Face Age Database : A Database for Face Recognition with Age Variation

[pdf]

[s2]

55c40cbcf49a0225e72d911d762c27bb1c2d14aa

ijb_c

IJB-C

IARPA Janus Benchmark C

IARPA Janus Benchmark - C: Face Dataset and Protocol

[pdf]

[s2]

57178b36c21fd7f4529ac6748614bb3374714e91

ilids_mcts

Imagery Library for Intelligent Detection Systems: The i-LIDS User Guide

Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems

[pdf]

[s2]

0297448f3ed948e136bb06ceff10eccb34e5bb77

ilids_vid_reid

iLIDS-VID

Person Re-Identication by Video Ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

images_of_groups

Images of Groups

Understanding Groups of Images of People

Understanding images of groups of people

[pdf]

[s2]

21d9d0deed16f0ad62a4865e9acf0686f4f15492

imm_face

IMM Face Dataset

The IMM Face Database - An Annotated Dataset of 240 Face Images

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

kdef

KDEF

The Karolinska Directed Emotional Faces – KDEF

Gaze fixation and the neural circuitry of face processing in autism

[pdf]

[s2]

93884e46c49f7ae1c7c34046fbc28882f2bd6341

kitti

KITTI

Vision meets Robotics: The KITTI Dataset

The Role of Machine Vision for Intelligent Vehicles

[pdf]

[s2]

35ba4ebfd017a56b51e967105af9ae273c9b0178

lfw

LFW

Labeled Faces in the Wild: A Survey

Labeled Faces in the Wild : A Survey

[pdf]

[s2]

7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22

lfw

LFW

Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

lfw

LFW

Labeled Faces in the Wild: Updates and New Reporting Procedures

Labeled Faces in the Wild : Updates and New Reporting Procedures

[pdf]

[s2]

University of Massachusetts

2d3482dcff69c7417c7b933f22de606a0e8e42d4

m2vts

The M2VTS Multimodal Face Database (Release 1.00)

The CAS-PEAL Large-Scale Chinese Face Database and Baseline Evaluations

[pdf]

[s2]

2485c98aa44131d1a2f7d1355b1e372f2bb148ad

m2vtsdb_extended

xm2vtsdb

XM2VTSDB: The Extended M2VTS Database

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

malf

MALF

Fine-grained Evaluation on Face Detection in the Wild.

Fine-grained evaluation on face detection in the wild

[pdf]

[s2]

Chinese Academy of Sciences

45e616093a92e5f1e61a7c6037d5f637aa8964af

mcgill

McGill Real World

Hierarchical Temporal Graphical Model for Head Pose Estimation and Subsequent Attribute Classification in Real-World Videos

Robust semi-automatic head pose labeling for real-world face video sequences

[pdf]

[s2]

McGill University

c570d1247e337f91e555c3be0e8c8a5aba539d9f

mot

MOT

Evaluating Multiple Object Tracking Performance: The CLEAR MOT Metrics

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mot

MOT

Performance Measures and a Data Set for Multi-Target, Multi-Camera Tracking

Learning to associate: HybridBoosted multi-target tracker for crowded scene

[pdf]

[s2]

5981e6479c3fd4e31644db35d236bfb84ae46514

mr2

MR2

The MR2: A multi-racial mega-resolution database of facial stimuli

The MR2: A multi-racial, mega-resolution database of facial stimuli.

[pdf]

[s2]

578d4ad74818086bb64f182f72e2c8bd31e3d426

mtfl

MTFL

Facial Landmark Detection by Deep Multi-task Learning

Learning Deep Representation for Face Alignment with Auxiliary Attributes

[pdf]

[s2]

a0fd85b3400c7b3e11122f44dc5870ae2de9009a

muct

MUCT

The MUCT Landmarked Face Database

Annotated Facial Landmarks in the Wild: A large-scale, real-world database for facial landmark localization

[pdf]

[s2]

a74251efa970b92925b89eeef50a5e37d9281ad0

multi_pie

MULTIPIE

Multi-PIE

Scheduling heterogeneous multi-cores through performance impact estimation (PIE)

[pdf]

[s2]

109df0e8e5969ddf01e073143e83599228a1163f

names_and_faces_news

News Dataset

Names and Faces

Names and faces in the news

[pdf]

[s2]

2fda164863a06a92d3a910b96eef927269aeb730

nova_emotions

Novaemötions Dataset

Competitive affective gamming: Winning with a smile

Competitive affective gaming: winning with a smile

[pdf]

[s2]

7f4040b482d16354d5938c1d1b926b544652bf5b

pilot_parliament

PPB

Gender Shades: Intersectional Accuracy Disparities in Commercial Gender Classication

Summary of Research on Informant Accuracy in Network Data, 11 and on the Reverse Small World Problem

[pdf]

[s2]

fb82681ac5d3487bd8e52dbb3d1fa220eeac855e

put_face

Put Face

The PUT face database

Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments

[pdf]

[s2]

370b5757a5379b15e30d619e4d3fb9e8e13f3256

scface

SCface

SCface – surveillance cameras face database

Large Variability Surveillance Camera Face Database

[pdf]

[s2]

f3b84a03985de3890b400b68e2a92c0a00afd9d0

sdu_vid

SDU-VID

Person reidentification by video ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

sheffield

Sheffield Face

Face Recognition: From Theory to Applications

Face Description with Local Binary Patterns: Application to Face Recognition

[pdf]

[s2]

3607afdb204de9a5a9300ae98aa4635d9effcda2

stanford_drone

Stanford Drone

Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes

Social LSTM: Human Trajectory Prediction in Crowded Spaces

[pdf]

[s2]

570f37ed63142312e6ccdf00ecc376341ec72b9f

stickmen_buffy

Buffy Stickmen

Learning to Parse Images of Articulated Objects

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

stickmen_pascal

Stickmen PASCAL

Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

stickmen_pascal

Stickmen PASCAL

Learning to Parse Images of Articulated Objects

Learning to parse images of articulated bodies

[pdf]

[s2]

6dd0597f8513dc100cd0bc1b493768cde45098a9

sun_attributes

SUN

SUN Attribute Database: +Paper Titles that do not match

Paper Titles that do not match

key	name	our title	found title			address	s2 id
ilids_mcts	i-LIDS	Imagery Library for Intelligent Detection Systems: The i-LIDS User Guide	Imagery Library for Intelligent Detection Systems (i-LIDS); A Standard for Testing Video Based Detection Systems	[pdf]	[s2]		0297448f3ed948e136bb06ceff10eccb34e5bb77
columbia_gaze	Columbia Gaze	Gaze Locking: Passive Eye Contact Detection for Human–Object Interaction	Gaze locking: passive eye contact detection for human-object interaction	[pdf]	[s2]		06f02199690961ba52997cde1527e714d2b3bf8f
d3dfacs	D3DFACS	A FACS Valid 3D Dynamic Action Unit database with Applications to 3D Dynamic Morphable Facial Modelling	A FACS valid 3D dynamic action unit database with applications to 3D dynamic morphable facial modeling	[pdf]	[s2]	Jacobs University	070de852bc6eb275d7ca3a9cdde8f6be8795d1a3
casablanca	Casablanca	Context-aware {CNNs} for person head detection	Context-Aware CNNs for Person Head Detection	[pdf]	[s2]		0ceda9dae8b9f322df65ca2ef02caca9758aec6f
afw	AFW	Face detection, pose estimation and landmark localization in the wild	Face detection, pose estimation, and landmark localization in the wild	[pdf]	[s2]	University of California, Irvine	0e986f51fe45b00633de9fd0c94d082d2be51406
frgc	FRGC	Overview of the Face Recognition Grand Challenge	Overview of the face recognition grand challenge	[pdf]	[s2]		18ae7c9a4bbc832b8b14bc4122070d7939f5e00e
images_of_groups	Images of Groups	Understanding Groups of Images of People	Understanding images of groups of people	[pdf]	[s2]		21d9d0deed16f0ad62a4865e9acf0686f4f15492
lfw	LFW	Labeled Faces in the Wild: Updates and New Reporting Procedures	Labeled Faces in the Wild : Updates and New Reporting Procedures	[pdf]	[s2]	University of Massachusetts	2d3482dcff69c7417c7b933f22de606a0e8e42d4
names_and_faces_news	News Dataset	Names and Faces	Names and faces in the news	[pdf]	[s2]		2fda164863a06a92d3a910b96eef927269aeb730
tiny_images	Tiny Images	80 million tiny images: a large dataset for non-parametric object and scene recognition	80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition	[pdf]	[s2]		31b58ced31f22eab10bd3ee2d9174e7c14c27c01
lfw	LFW	Labeled Faces in the Wild: A Database for Studying Face Recognition in Unconstrained Environments	Labeled Faces in the Wild : A Database for Studying Face Recognition in Unconstrained Environments	[pdf]	[s2]		370b5757a5379b15e30d619e4d3fb9e8e13f3256
georgia_tech_face_database	Georgia Tech Face	Maximum likelihood training of the embedded HMM for face detection and recognition	MAXIMUM LIKELIHOOD TRAINING OF THE EMBEDDED HMM FOR FACE DETECTION AND RECOGNITION Ara V. Ne an and Monson H. Hayes III Center for Signal and Image Processing School of Electrical and Computer Engineering	[pdf]	[s2]		3dc3f0b64ef80f573e3a5f96e456e52ee980b877
malf	MALF	Fine-grained Evaluation on Face Detection in the Wild.	Fine-grained evaluation on face detection in the wild	[pdf]	[s2]	Chinese Academy of Sciences	45e616093a92e5f1e61a7c6037d5f637aa8964af
am_fed	AM-FED	Affectiva MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected “In the Wild”	Affectiva-MIT Facial Expression Dataset (AM-FED): Naturalistic and Spontaneous Facial Expressions Collected "In-the-Wild"	[pdf]	[s2]		47aeb3b82f54b5ae8142b4bdda7b614433e69b9a
cmu_pie	CMU PIE	The CMU Pose, Illumination, and Expression Database	The CMU Pose, Illumination, and Expression (PIE) Database	[pdf]	[s2]		4d423acc78273b75134e2afd1777ba6d3a398973
multi_pie	MULTIPIE	Multi-PIE	The CMU Pose, Illumination, and Expression (PIE) Database	[pdf]	[s2]		4d423acc78273b75134e2afd1777ba6d3a398973
3dddb_unconstrained	3D Dynamic	A 3D Dynamic Database for Unconstrained Face Recognition	A 3 D Dynamic Database for Unconstrained Face Recognition	[pdf]	[s2]		4d4bb462c9f1d4e4ab1e4aa6a75cc0bc71b38461
cfd	CFD	The Chicago face database: A free stimulus set of faces and norming data	The Chicago face database: A free stimulus set of faces and norming data.	[pdf]	[s2]		4df3143922bcdf7db78eb91e6b5359d6ada004d2
dartmouth_children	Dartmouth Children	The Dartmouth Database of Children's Faces: Acquisition and validation of a new face stimulus set	The Dartmouth Database of Children’s Faces: Acquisition and Validation of a New Face Stimulus Set	[pdf]	[s2]		4e6ee936eb50dd032f7138702fa39b7c18ee8907
ifad	IFAD	Indian Face Age Database: A Database for Face Recognition with Age Variation	Indian Face Age Database : A Database for Face Recognition with Age Variation	[pdf]	[s2]		55c40cbcf49a0225e72d911d762c27bb1c2d14aa
stanford_drone	Stanford Drone	Learning Social Etiquette: Human Trajectory Prediction In Crowded Scenes	Social LSTM: Human Trajectory Prediction in Crowded Spaces	[pdf]	[s2]		570f37ed63142312e6ccdf00ecc376341ec72b9f
ijb_c	IJB-C	IARPA Janus Benchmark C	IARPA Janus Benchmark - C: Face Dataset and Protocol	[pdf]	[s2]		57178b36c21fd7f4529ac6748614bb3374714e91
mr2	MR2	The MR2: A multi-racial mega-resolution database of facial stimuli	The MR2: A multi-racial, mega-resolution database of facial stimuli.	[pdf]	[s2]		578d4ad74818086bb64f182f72e2c8bd31e3d426
cvc_01_barcelona	CVC-01	Adaptive Image Sampling and Windows Classification for On-board Pedestrian Detection	Adaptive Image Sampling and Windows Classification for On – board Pedestrian Detection	[pdf]	[s2]		57fe081950f21ca03b5b375ae3e84b399c015861
viper	VIPeR	Evaluating Appearance Models for Recognition, Reacquisition, and Tracking	Evaluating Appearance Models for Recognition , Reacquisition , and Tracking	[pdf]	[s2]		6273b3491e94ea4dd1ce42b791d77bdc96ee73a8
alert_airport	ALERT Airport	A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets	A Systematic Evaluation and Benchmark for Person Re-Identification: Features, Metrics, and Datasets.	[pdf]	[s2]		6403117f9c005ae81f1e8e6d1302f4a045e3d99d
afad	AFAD	Ordinal Regression with a Multiple Output CNN for Age Estimation	Ordinal Regression with Multiple Output CNN for Age Estimation	[pdf]	[s2]		6618cff7f2ed440a0d2fa9e74ad5469df5cdbe4c
stickmen_buffy	Buffy Stickmen	Learning to Parse Images of Articulated Objects	Learning to parse images of articulated bodies	[pdf]	[s2]		6dd0597f8513dc100cd0bc1b493768cde45098a9
stickmen_pascal	Stickmen PASCAL	Clustered Pose and Nonlinear Appearance Models for Human Pose Estimation	Learning to parse images of articulated bodies	[pdf]	[s2]		6dd0597f8513dc100cd0bc1b493768cde45098a9
stickmen_pascal	Stickmen PASCAL	Learning to Parse Images of Articulated Objects	Learning to parse images of articulated bodies	[pdf]	[s2]		6dd0597f8513dc100cd0bc1b493768cde45098a9
umd_faces	UMD	The Do's and Don'ts for CNN-based Face Verification	The Do’s and Don’ts for CNN-Based Face Verification	[pdf]	[s2]		71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6
fddb	FDDB	FDDB: A Benchmark for Face Detection in Unconstrained Settings	A Benchmark for Face Detection in Unconstrained Settings	[pdf]	[s2]	University of Massachusetts	75da1df4ed319926c544eefe17ec8d720feef8c0
wildtrack	WildTrack	WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	[pdf]	[s2]		77c81c13a110a341c140995bedb98101b9e84f7f
lfw	LFW	Labeled Faces in the Wild: A Survey	Labeled Faces in the Wild : A Survey	[pdf]	[s2]		7de6e81d775e9cd7becbfd1bd685f4e2a5eebb22
nova_emotions	Novaemötions Dataset	Competitive affective gamming: Winning with a smile	Competitive affective gaming: winning with a smile	[pdf]	[s2]		7f4040b482d16354d5938c1d1b926b544652bf5b
sun_attributes	SUN	SUN Attribute Database: Discovering, Annotating, and Recognizing Scene Attributes	SUN attribute database: Discovering, annotating, and recognizing scene attributes	[pdf]	[s2]		833fa04463d90aab4a9fe2870d480f0b40df446e
tiny_images	Tiny Images	80 million tiny images: a large dataset for non-parametric object and scene recognition	80 Million Tiny Images: A Large Data Set for Nonparametric Object and Scene Recognition	[pdf]	[s2]		31b58ced31f22eab10bd3ee2d9174e7c14c27c01
umd_faces	UMD	The Do's and Don'ts for CNN-based Face Verification	The Do’s and Don’ts for CNN-Based Face Verification	[pdf]	[s2]		71b7fc715e2f1bb24c0030af8d7e7b6e7cd128a6
viper	VIPeR	Evaluating Appearance Models for Recognition, Reacquisition, and Tracking	Evaluating Appearance Models for Recognition , Reacquisition , and Tracking	[pdf]	[s2]		6273b3491e94ea4dd1ce42b791d77bdc96ee73a8
who_goes_there	WGT	Who Goes There? Approaches to Mapping Facial Appearance Diversity	Who goes there?: approaches to mapping facial appearance diversity	[pdf]	[s2]		9b9bf5e623cb8af7407d2d2d857bc3f1b531c182
wildtrack	WildTrack	WILDTRACK: A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	WILDTRACK : A Multi-camera HD Dataset for Dense Unscripted Pedestrian Detection	[pdf]	[s2]		77c81c13a110a341c140995bedb98101b9e84f7f

\ No newline at end of file +discovering, annotating, and recognizing scene attributes&sort=relevance" target="_blank">[s2]

833fa04463d90aab4a9fe2870d480f0b40df446e

10k_US_adult_faces

10K US Adult Faces

The intrinsic memorability of face images

The intrinsic memorability of face photographs.

[pdf]

[s2]

8b2dd5c61b23ead5ae5508bb8ce808b5ea266730

fei

FEI

Captura e Alinhamento de Imagens: Um Banco de Faces Brasileiro

A new ranking method for principal components analysis and its application to face image analysis

[pdf]

[s2]

8b56e33f33e582f3e473dba573a16b598ed9bcdc

ilids_vid_reid

iLIDS-VID

Person Re-Identication by Video Ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

sdu_vid

SDU-VID

Person reidentification by video ranking

Person Re-identification by Video Ranking

[pdf]

[s2]

98bb029afe2a1239c3fdab517323066f0957b81b

who_goes_there

WGT

Who Goes There? Approaches to Mapping Facial Appearance Diversity

Who goes there?: approaches to mapping facial appearance diversity

[pdf]

[s2]

9b9bf5e623cb8af7407d2d2d857bc3f1b531c182

bp4d_spontanous

BP4D-Spontanous

A high resolution spontaneous 3D dynamic facial expression database

A high-resolution spontaneous 3D dynamic facial expression database

[pdf]

[s2]

SUNY Binghamton

b91f54e1581fbbf60392364323d00a0cd43e493c

hda_plus

HDA+

A Multi-camera video data set for research on High-Definition surveillance

HDA dataset-DRAFT 1 A Multi-camera video data set for research on High-Definition surveillance

[pdf]

[s2]

bd88bb2e4f351352d88ee7375af834360e223498

\ No newline at end of file diff --git a/scraper/s2-final-report.py b/scraper/s2-final-report.py index 3cceff43..675709ea 100644 --- a/scraper/s2-final-report.py +++ b/scraper/s2-final-report.py @@ -183,6 +183,8 @@ def load_megapixels_lookup(): rec = {} for index, key in enumerate(keys): rec[key] = row[index] + if rec['paper_id'] == "": + continue paper_key = rec['key'] if paper_key not in lookup: rec['paper_ids'] = [] diff --git a/scraper/s2-geocode-server.py b/scraper/s2-geocode-server.py index 021921fe..1c624a52 100644 --- a/scraper/s2-geocode-server.py +++ b/scraper/s2-geocode-server.py @@ -52,3 +52,7 @@ def list_citations(citation): def geocode_paper(): return jsonify({ }) + +if __name__=="__main__": + app.run("0.0.0.0", debug=False) + diff --git a/scraper/s2-papers.py b/scraper/s2-papers.py index 58aebcc6..744454b7 100644 --- a/scraper/s2-papers.py +++ b/scraper/s2-papers.py @@ -28,7 +28,11 @@ def fetch_papers(): name = line[1] title = line[2] paper_id = line[3] + if paper_id == '': + continue paper = fetch_paper(s2, paper_id) + if paper is None: + continue db_paper = load_paper(paper_id) pdf_link = db_paper.pdf_link if db_paper else "" diff --git a/scraper/util.py b/scraper/util.py index 2d7c2ccb..6f3fc08b 100644 --- a/scraper/util.py +++ b/scraper/util.py @@ -331,11 +331,11 @@ def fetch_paper(s2, paper_id): print(paper_id) paper = s2.paper(paper_id) if paper is None: - print("Got none paper??") + print("Paper not found: {}".format(paper_id)) # time.sleep(random.randint(1, 2)) paper = s2.paper(paper_id) if paper is None: - print("Paper not found") + # print("Paper not found") return None write_json(paper_fn, paper) # time.sleep(random.randint(1, 2)) -- cgit v1.2.3-70-g09d2 From dc1889f15ab1b1338c557cda0b1bcd989e1fdf9b Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Wed, 13 Feb 2019 02:00:50 +0100 Subject: update --- client/geocode/geocode.component.js | 9 +++++ package-lock.json | 60 +++++++++++++++++++++++++++++ package.json | 4 +- scraper/reports/geocode_papers.html | 1 + scraper/s2-final-report.py | 8 ++-- scraper/s2-geocode-server.py | 40 +++++++++++-------- scraper/util.py | 3 +- site/datasets/final/feret.json | 2 +- site/datasets/final/ijb_c.json | 2 +- site/datasets/final/lfw.json | 2 +- site/datasets/final/megaface.json | 2 +- site/datasets/final/voc.json | 2 +- site/datasets/final/youtube_makeup.json | 2 +- site/datasets/unknown/adience.json | 2 +- site/datasets/unknown/aflw.json | 2 +- site/datasets/unknown/casia_webface.json | 2 +- site/datasets/unknown/celeba.json | 2 +- site/datasets/unknown/cofw.json | 2 +- site/datasets/unknown/feret.json | 2 +- site/datasets/unknown/helen.json | 2 +- site/datasets/unknown/ijb_c.json | 2 +- site/datasets/unknown/images_of_groups.json | 2 +- site/datasets/unknown/imdb_wiki.json | 2 +- site/datasets/unknown/lfw.json | 2 +- site/datasets/unknown/megaface.json | 2 +- site/datasets/unknown/morph.json | 2 +- site/datasets/unknown/morph_nc.json | 2 +- site/datasets/unknown/msceleb.json | 2 +- site/datasets/unknown/pipa.json | 2 +- site/datasets/unknown/pubfig_83.json | 2 +- site/datasets/unknown/uccs.json | 2 +- site/datasets/unknown/umd_faces.json | 2 +- site/datasets/unknown/vgg_faces2.json | 2 +- webpack.geocode.dev.js | 2 +- 34 files changed, 130 insertions(+), 49 deletions(-) (limited to 'scraper/s2-geocode-server.py') diff --git a/client/geocode/geocode.component.js b/client/geocode/geocode.component.js index a6766bec..e57d238d 100644 --- a/client/geocode/geocode.component.js +++ b/client/geocode/geocode.component.js @@ -3,10 +3,19 @@ import React, { Component } from 'react' import Autocomplete from './autocomplete.component' class GeocodeContainer extends Component { + // constructor() { + // super() + // } render() { // const { } = this.props return (

+ +

) } diff --git a/package-lock.json b/package-lock.json index 187e090a..a4d114fc 100644 --- a/package-lock.json +++ b/package-lock.json @@ -7163,6 +7163,66 @@ } } }, + "react-router": { + "version": "4.3.1", + "resolved": "https://registry.npmjs.org/react-router/-/react-router-4.3.1.tgz", + "integrity": "sha512-yrvL8AogDh2X42Dt9iknk4wF4V8bWREPirFfS9gLU1huk6qK41sg7Z/1S81jjTrGHxa3B8R3J6xIkDAA6CVarg==", + "requires": { + "history": "^4.7.2", + "hoist-non-react-statics": "^2.5.0", + "invariant": "^2.2.4", + "loose-envify": "^1.3.1", + "path-to-regexp": "^1.7.0", + "prop-types": "^15.6.1", + "warning": "^4.0.1" + }, + "dependencies": { + "isarray": { + "version": "0.0.1", + "resolved": "https://registry.npmjs.org/isarray/-/isarray-0.0.1.tgz", + "integrity": "sha1-ihis/Kmo9Bd+Cav8YDiTmwXR7t8=" + }, + "path-to-regexp": { + "version": "1.7.0", + "resolved": "https://registry.npmjs.org/path-to-regexp/-/path-to-regexp-1.7.0.tgz", + "integrity": "sha1-Wf3g9DW62suhA6hOnTvGTpa5k30=", + "requires": { + "isarray": "0.0.1" + } + }, + "warning": { + "version": "4.0.3", + "resolved": "https://registry.npmjs.org/warning/-/warning-4.0.3.tgz", + "integrity": "sha512-rpJyN222KWIvHJ/F53XSZv0Zl/accqHR8et1kpaMTD/fLCRxtV8iX8czMzY7sVZupTI3zcUTg8eycS2kNF9l6w==", + "requires": { + "loose-envify": "^1.0.0" + } + } + } + }, + "react-router-dom": { + "version": "4.3.1", + "resolved": "https://registry.npmjs.org/react-router-dom/-/react-router-dom-4.3.1.tgz", + "integrity": "sha512-c/MlywfxDdCp7EnB7YfPMOfMD3tOtIjrQlj/CKfNMBxdmpJP8xcz5P/UAFn3JbnQCNUxsHyVVqllF9LhgVyFCA==", + "requires": { + "history": "^4.7.2", + "invariant": "^2.2.4", + "loose-envify": "^1.3.1", + "prop-types": "^15.6.1", + "react-router": "^4.3.1", + "warning": "^4.0.1" + }, + "dependencies": { + "warning": { + "version": "4.0.3", + "resolved": "https://registry.npmjs.org/warning/-/warning-4.0.3.tgz", + "integrity": "sha512-rpJyN222KWIvHJ/F53XSZv0Zl/accqHR8et1kpaMTD/fLCRxtV8iX8czMzY7sVZupTI3zcUTg8eycS2kNF9l6w==", + "requires": { + "loose-envify": "^1.0.0" + } + } + } + }, "react-spin": { "version": "0.6.2", "resolved": "https://registry.npmjs.org/react-spin/-/react-spin-0.6.2.tgz", diff --git a/package.json b/package.json index 6ff9dac5..0cc38ef6 100644 --- a/package.json +++ b/package.json @@ -9,7 +9,8 @@ "build": "NODE_ENV=production webpack --config ./webpack.config.prod.js", "deploy": "NODE_ENV=production webpack --config ./webpack.config.prod.js && git commit -am 'deploy' && git push origin master && ssh vframe@vframe ./restart.sh", "watchSplash": "NODE_ENV=development webpack --config ./webpack.splash.dev.js --colors --watch", - "buildSplash": "NODE_ENV=production webpack --config ./webpack.splash.prod.js" + "buildSplash": "NODE_ENV=production webpack --config ./webpack.splash.prod.js", + "watchGeocode": "NODE_ENV=development webpack --config ./webpack.geocode.dev.js --colors --watch" }, "repository": { "type": "git", @@ -48,6 +49,7 @@ "react-dom": "^16.3.0", "react-hot-loader": "^4.3.0", "react-redux": "^5.0.7", + "react-router-dom": "^4.3.1", "react-spin": "^0.6.2", "redux": "^4.0.0", "redux-thunk": "^2.3.0", diff --git a/scraper/reports/geocode_papers.html b/scraper/reports/geocode_papers.html index 529ee9c7..84ffe356 100644 --- a/scraper/reports/geocode_papers.html +++ b/scraper/reports/geocode_papers.html @@ -33,5 +33,6 @@ html,body { margin: 0; padding: 0; width: 100%; height: 100%; }

+ diff --git a/scraper/s2-final-report.py b/scraper/s2-final-report.py index 675709ea..58ac481f 100644 --- a/scraper/s2-final-report.py +++ b/scraper/s2-final-report.py @@ -32,8 +32,8 @@ def process_paper(row, addresses): res = process_single_paper(row, paper_id, addresses, aggregate_citations, unknown_citations) if res: papers.append(res) - if res['address']: - address = res['address'] + if res['address']: + address = res['address'] if not len(papers): return with open('{}/{}.json'.format(DIR_PUBLIC_CITATIONS, row['key']), 'w') as f: @@ -48,9 +48,7 @@ def process_paper(row, addresses): json.dump({ 'id': papers[0]['paper_id'], 'paper': papers[0], - 'address': address, - 'additional_papers': papers[1:], - 'citations': [aggregate_citations[key] for key in aggregate_citations.keys()], + 'citations': [unknown_citations[key] for key in unknown_citations.keys()], }, f) def process_single_paper(row, paper_id, addresses, aggregate_citations, unknown_citations): diff --git a/scraper/s2-geocode-server.py b/scraper/s2-geocode-server.py index 1c624a52..0b1b0937 100644 --- a/scraper/s2-geocode-server.py +++ b/scraper/s2-geocode-server.py @@ -13,15 +13,19 @@ load_dotenv() from util import * -app = Flask(__name__, static_url_path="/reports/", static_folder="reports") +locations_worksheet = fetch_worksheet('paper_locations') + +app = Flask(__name__, static_url_path="/reports", static_folder=os.path.abspath("reports")) # static api route @app.route('/', methods=['GET']) def index(): - return app.send_static_file('reports/geocode-papers.html') + return app.send_static_file('geocode_papers.html') + +@app.errorhandler(404) +def page_not_found(e): + return app.send_static_file('geocode_papers.html') -# route to list the papers -# route to get all the un-geocoded citations for a paper # route to get all the manually geocoded IDs (to dedupe) # route to add a geocoding for a paper @@ -36,23 +40,29 @@ def list_locations(): @app.route('/api/papers', methods=['GET']) def list_papers(): lookup_keys, lines = fetch_google_sheet('citation_lookup') - lookup = {} + paper_lookup = {} for line in lines: - lookup[line[0]] = line - return jsonify({ - 'papers': papers, - }) - -@app.route('/api/papers/:citation/', methods=['GET']) -def list_citations(citation): + paper_lookup[line[0]] = line return jsonify({ + 'papers': paper_lookup, }) -@app.route('/api/geocode', methods=['POST']) -def geocode_paper(): +@app.route('/api/address', methods=['POST']) +def add_address(): + # id, title, institution_1, institution_2, institution_3, institution_4, notes + locations_worksheet.insert_row([ + request.form['paper_id'], + request.form['title'], + request.form['institution_1'], + request.form['institution_2'], + request.form['institution_3'], + request.form['institution_4'], + request.form['notes'], + ]) return jsonify({ + 'status': 'ok' }) if __name__=="__main__": - app.run("0.0.0.0", debug=False) + app.run("0.0.0.0", debug=False) diff --git a/scraper/util.py b/scraper/util.py index 6f3fc08b..9b47510a 100644 --- a/scraper/util.py +++ b/scraper/util.py @@ -343,7 +343,8 @@ def fetch_paper(s2, paper_id): def fetch_spreadsheet(): scope = ['https://spreadsheets.google.com/feeds','https://www.googleapis.com/auth/drive'] - credentials = ServiceAccountCredentials.from_json_keyfile_name('./.creds/Megapixels-ef28f91112a9.json', scope) + path = os.path.dirname(os.path.abspath(__file__)) + credentials = ServiceAccountCredentials.from_json_keyfile_name(os.path.join(path, '.creds/Megapixels-ef28f91112a9.json'), scope) docid = "1denb7TjYsN9igHyvYah7fQ0daABW32Z30lwV7QrDJQc" client = gspread.authorize(credentials) spreadsheet = client.open_by_key(docid) diff --git a/site/datasets/final/feret.json b/site/datasets/final/feret.json index a6584c3b..27cffaec 100644 --- a/site/datasets/final/feret.json +++ b/site/datasets/final/feret.json @@ -1 +1 @@ -{"id": "0c4a139bb87c6743c7905b29a3cfec27a5130652", "paper": {"paper_id": "0c4a139bb87c6743c7905b29a3cfec27a5130652", "key": "feret", "title": "The FERET Verification Testing Protocol for Face Recognition Algorithms", "year": 1998, "pdf": "http://pdfs.semanticscholar.org/0c4a/139bb87c6743c7905b29a3cfec27a5130652.pdf", "address": "", "name": "FERET"}, "address": null, "additional_papers": [{"paper_id": "dc8b25e35a3acb812beb499844734081722319b4", "key": "feret", "title": "The FERET Promising Research database and evaluation procedure for face - 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