1 files changed, 0 insertions, 72 deletions
diff --git a/reports/stats/unknown_papers.csv b/reports/stats/unknown_papers.csv
index 04d23f8d..92a64dac 100644
--- a/reports/stats/unknown_papers.csv
+++ b/reports/stats/unknown_papers.csv
@@ -809,10 +809,6 @@ Veracruz, M´exico"
 Discriminative Block-Diagonal Representation
 Learning for Image Recognition
 Zheng Zhang, Yong Xu, Senior Member, IEEE, Ling Shao, Senior Member, IEEE, Jian Yang, Member, IEEE"
-68e9c837431f2ba59741b55004df60235e50994d,Detecting Faces Using Region-based Fully Convolutional Networks,"Detecting Faces Using Region-based Fully
-Convolutional Networks
-Yitong Wang Xing Ji Zheng Zhou Hao Wang Zhifeng Li∗
-Tencent AI Lab, China"
 685f8df14776457c1c324b0619c39b3872df617b,Face Recognition with Preprocessing and Neural Networks,"Master of Science Thesis in Electrical Engineering
 Department of Electrical Engineering, Linköping University, 2016
 Face Recognition with
@@ -824,12 +820,6 @@ Sushil Bhattacharjee Amir Mohammadi
 S´ebastien Marcel
 Idiap Research Institute. Centre du Parc, Rue Marconi 19, Martigny (VS), Switzerland
 {sushil.bhattacharjee; amir.mohammadi;"
-687e17db5043661f8921fb86f215e9ca2264d4d2,A robust elastic and partial matching metric for face recognition,"A Robust Elastic and Partial Matching Metric for Face Recognition
-Gang Hua
-Amir Akbarzadeh
-Microsoft Corporate
-One Microsoft Way, Redmond, WA 98052
-{ganghua,"
 688754568623f62032820546ae3b9ca458ed0870,Resting high frequency heart rate variability is not associated with the recognition of emotional facial expressions in healthy human adults,"ioRxiv preprint first posted online Sep. 27, 2016;
 http://dx.doi.org/10.1101/077784
 The copyright holder for this preprint (which was not
@@ -2380,13 +2370,6 @@ ode of this work is available at https://github.com/pengsun/bpcpr5."
 93675f86d03256f9a010033d3c4c842a732bf661,Localized Growth and Characterization of Silicon Nanowires,Universit´edesSciencesetTechnologiesdeLilleEcoleDoctoraleSciencesPourl’ing´enieurUniversit´eLilleNord-de-FranceTHESEPr´esent´ee`al’Universit´edesSciencesetTechnologiesdeLillePourobtenirletitredeDOCTEURDEL’UNIVERSIT´ESp´ecialit´e:MicroetNanotechnologieParTaoXULocalizedgrowthandcharacterizationofsiliconnanowiresSoutenuele25Septembre2009Compositiondujury:Pr´esident:TuamiLASRIRapporteurs:ThierryBARONHenriMARIETTEExaminateurs:EricBAKKERSXavierWALLARTDirecteurdeth`ese:BrunoGRANDIDIER
 936c7406de1dfdd22493785fc5d1e5614c6c2882,Detecting Visual Text,"012 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 762–772,
 Montr´eal, Canada, June 3-8, 2012. c(cid:13)2012 Association for Computational Linguistics"
-93721023dd6423ab06ff7a491d01bdfe83db7754,Robust Face Alignment Using Convolutional Neural Networks,"ROBUST FACE ALIGNMENT USING CONVOLUTIONAL NEURAL
-NETWORKS
-Stefan Duffner and Christophe Garcia
-Orange Labs, 4, Rue du Clos Courtel, 35512 Cesson-S´evign´e, France
-{stefan.duffner,
-Keywords:
-Face alignment, Face registration, Convolutional Neural Networks."
 93cbb3b3e40321c4990c36f89a63534b506b6daf,Learning from examples in the small sample case: face expression recognition,"IEEE TRANSACTIONS ON SYSTEMS, MAN, AND CYBERNETICS—PART B: CYBERNETICS, VOL. 35, NO. 3, JUNE 2005
 Learning From Examples in the Small Sample Case:
 Face Expression Recognition
@@ -2752,9 +2735,6 @@ for Expression Recognition
 S.P. Khandait1, P.D. Khandait2 and Dr.R.C.Thool2
 Deptt. of Info.Tech., K.D.K.C.E., Nagpur, India
 2Deptt.of Electronics Engg., K.D.K.C.E., Nagpur, India, 2Deptt. of Info.Tech., SGGSIET, Nanded"
-3399f8f0dff8fcf001b711174d29c9d4fde89379,Face R-CNN,"Face R-CNN
-Hao Wang Zhifeng Li∗ Xing Ji Yitong Wang
-Tencent AI Lab, China"
 333aa36e80f1a7fa29cf069d81d4d2e12679bc67,Suggesting Sounds for Images from Video Collections,"Suggesting Sounds for Images
 from Video Collections
 Matthias Sol`er1, Jean-Charles Bazin2, Oliver Wang2, Andreas Krause1 and
@@ -4812,11 +4792,6 @@ Alaaeldin El-Nouby∗†, Graham W. Taylor∗†‡
 School of Engineering, University of Guelph
 Vector Institute for Artiﬁcial Intelligence
 Canadian Institute for Advanced Research"
-f437b3884a9e5fab66740ca2a6f1f3a5724385ea,Human identification technical challenges,"Human Identification Technical Challenges
-P. Jonathon Phillips
-DARPA
-701 N. Fairfax Dr
-Arlington, VA 22203"
 f412d9d7bc7534e7daafa43f8f5eab811e7e4148,Running Head : Anxiety and Emotional Faces in WS 2,"Durham Research Online
 Deposited in DRO:
 6 December 2014
@@ -9128,18 +9103,6 @@ Algorithm
 Shaik. Kartheek.*1, A.Srinivasa Reddy*2
 M.Tech Scholar, Dept of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India.
 Associate Professor, Department of CSE, QISCET, ONGOLE, Dist: Prakasam, AP, India"
-3803b91e784922a2dacd6a18f61b3100629df932,Temporal Multimodal Fusion for Video Emotion Classification in the Wild,"Temporal Multimodal Fusion
-for Video Emotion Classification in the Wild
-Valentin Vielzeuf∗
-Orange Labs
-Cesson-Sévigné, France
-Stéphane Pateux
-Orange Labs
-Cesson-Sévigné, France
-Frédéric Jurie
-Normandie Univ., UNICAEN,
-ENSICAEN, CNRS
-Caen, France"
 38eea307445a39ee7902c1ecf8cea7e3dcb7c0e7,Multi-distance Support Matrix Machines,"Noname manuscript No.
 (will be inserted by the editor)
 Multi-distance Support Matrix Machine
@@ -9179,10 +9142,6 @@ The Research Portal is Queen's institutional repository that provides access to
 ensure that content in the Research Portal does not infringe any person's rights, or applicable UK laws. If you discover content in the
 Research Portal that you believe breaches copyright or violates any law, please contact
 Download date:05. Nov. 2018"
-38183fe28add21693729ddeaf3c8a90a2d5caea3,Scale-Aware Face Detection,"Scale-Aware Face Detection
-Zekun Hao1, Yu Liu1, Hongwei Qin2, Junjie Yan2, Xiu Li2, Xiaolin Hu2
-SenseTime, 2Tsinghua University
-{haozekun,"
 3802da31c6d33d71b839e260f4022ec4fbd88e2d,Deep Attributes for One-Shot Face Recognition,"Deep Attributes for One-Shot Face Recognition
 Aishwarya Jadhav1,3, Vinay P. Namboodiri2, and K. S. Venkatesh 3
 Xerox Research Center India, 2Department of Computer Science,
@@ -9306,12 +9265,6 @@ PG Student at MET’s IOE Bhujbal Knowledge City,
 PG Student at MET’s IOE Bhujbal Knowledge City,
 Nasik, Maharashtra, India,
 Nasik, Maharashtra, India,"
-6e9a8a34ab5b7cdc12ea52d94e3462225af2c32c,Fusing Aligned and Non-aligned Face Information for Automatic Affect Recognition in the Wild: A Deep Learning Approach,"Fusing Aligned and Non-Aligned Face Information
-for Automatic Affect Recognition in the Wild: A Deep Learning Approach
-Bo-Kyeong Kim, Suh-Yeon Dong, Jihyeon Roh, Geonmin Kim, Soo-Young Lee
-Computational NeuroSystems Laboratory (CNSL)
-Korea Advanced Institute of Science and Technology (KAIST)
-{bokyeong1015, {rohleejh, gmkim90,"
 6e3a181bf388dd503c83dc324561701b19d37df1,Finding a low-rank basis in a matrix subspace,"Finding a low-rank basis in a matrix subspace
 Yuji Nakatsukasa · Tasuku Soma ·
 Andr´e Uschmajew"
@@ -10645,13 +10598,6 @@ Image Processing and Analysis
 Laboratory, LAPI
 University “Politehnica” of Bucharest
 Bucharest, Romania"
-37c8514df89337f34421dc27b86d0eb45b660a5e,Facial Landmark Tracking by Tree-Based Deformable Part Model Based Detector,"Facial Landmark Tracking by Tree-based Deformable Part Model
-Based Detector
-Michal Uˇriˇc´aˇr, Vojtˇech Franc, and V´aclav Hlav´aˇc
-Center for Machine Perception, Department of Cybernetics
-Faculty of Electrical Engineering, Czech Technical University in Prague
-66 27 Prague 6, Technick´a 2, Czech Republic
-{uricamic, xfrancv,"
 374c7a2898180723f3f3980cbcb31c8e8eb5d7af,Facial Expression Recognition in Videos using a Novel Multi-Class Support Vector Machines Variant,"FACIAL EXPRESSION RECOGNITION IN VIDEOS USING A NOVEL MULTI-CLASS
 SUPPORT VECTOR MACHINES VARIANT
 Irene Kotsiay, Nikolaos Nikolaidisy and Ioannis Pitasy
@@ -13622,11 +13568,6 @@ Regressions
 Martin Penev1*, Ognian Boumbarov2
 Faculty of Telecommunications, Technical University, Sofia, Bulgaria
 Faculty of Telecommunications, Technical University, Sofia, Bulgaria"
-f0a3f12469fa55ad0d40c21212d18c02be0d1264,Sparsity Sharing Embedding for Face Verification,"Sparsity Sharing Embedding for Face
-Veriﬁcation
-Donghoon Lee, Hyunsin Park, Junyoung Chung,
-Youngook Song, and Chang D. Yoo
-Department of Electrical Engineering, KAIST, Daejeon, Korea"
 f740bac1484f2f2c70777db6d2a11cf4280081d6,Soft Locality Preserving Map (SLPM) for Facial Expression Recognition,"Soft Locality Preserving Map (SLPM) for Facial Expression
 Recognition
 Cigdem Turana,*, Kin-Man Lama, Xiangjian Heb
@@ -15452,10 +15393,6 @@ Brian O’Connor and Kaushik Roy
 Department of Computer Science,
 North Carolina A&T State University,
 Greensboro, NC 27411"
-849f891973ad2b6c6f70d7d43d9ac5805f1a1a5b,ResNet Backbone Proposals Classification Loss Regression Loss Classification Loss Regression Loss RPN Classification Branch Box Regression Branch Conv Conv,"Detecting Faces Using Region-based Fully
-Convolutional Networks
-Yitong Wang Xing Ji Zheng Zhou Hao Wang Zhifeng Li∗
-Tencent AI Lab, China"
 4adca62f888226d3a16654ca499bf2a7d3d11b71,Models of Semantic Representation with Visual Attributes,"Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics, pages 572–582,
 Soﬁa, Bulgaria, August 4-9 2013. c(cid:13)2013 Association for Computational Linguistics"
 4a2d54ea1da851151d43b38652b7ea30cdb6dfb2,Direct recognition of motion-blurred faces,"Direct Recognition of Motion Blurred Faces
@@ -16655,11 +16592,6 @@ sking the patients to ﬁll out a questionnaire, as it is currently done [7]. Fa
 recognition may enable a new generation of teaching systems to adapt to the expression
 of their students in the way good teachers do [61]. Expression recognition could be used
 to assess the fatigue of drivers and air-pilots [58, 59]. Daily-life robots with automatic"
-40273657e6919455373455bd9a5355bb46a7d614,Anonymizing k Facial Attributes via Adversarial Perturbations,"Anonymizing k-Facial Attributes via Adversarial Perturbations
-Saheb Chhabra1, Richa Singh1, Mayank Vatsa1 and Gaurav Gupta2
-IIIT Delhi, New Delhi, India
-Ministry of Electronics and Information Technology, New Delhi, India
-{sahebc, rsingh,"
 40b10e330a5511a6a45f42c8b86da222504c717f,Implementing the Viola-Jones Face Detection Algorithm,"Implementing the Viola-Jones
 Face Detection Algorithm
 Ole Helvig Jensen
@@ -17666,10 +17598,6 @@ Michel F. Valstar, Bihan Jiang, Marc Mehu, Maja Pantic, and Klaus Scherer"
 2597b0dccdf3d89eaffd32e202570b1fbbedd1d6,Towards Predicting the Likeability of Fashion Images,"Towards predicting the likeability of fashion images
 Jinghua Wang, Abrar Abdul Nabi, Gang Wang, Member, IEEE, Chengde Wan, Tian-Tsong Ng, Member, IEEE,"
 25982e2bef817ebde7be5bb80b22a9864b979fb0,Facial Feature Tracking Under Varying Facial Expressions and Face Poses Based on Restricted Boltzmann Machines,"(a)26facialfeaturepointsthatwetrack(b)oneexamplesequenceFigure1.Facialfeaturepointtrackingunderexpressionvariationandocclusion.Inrecentyears,thesemodelshavebeenusedexplicitlytohandletheshapevariations[17][5].Thenonlinearityem-beddedinRBManditsvariantsmakesthemmoreeffectiveandefﬁcienttorepresentthenonrigiddeformationsofob-jectscomparedtothelinearmethods.Theirlargenumberofhiddennodesanddeeparchitecturesalsocanimposesufﬁ-cientconstraintsaswellasenoughdegreesoffreedomsintotherepresentationsofthetargetobjects.Inthispaper,wepresentaworkthatcaneffectivelytrackfacialfeaturepointsusingfaceshapepriormodelsthatareconstructedbasedonRBM.Thefacialfeaturetrackercantrack26facialfeaturepoints(Fig.1(a))eveniffaceshavedifferentfacialexpressions,varyingposes,orocclu-sion(Fig.1(b)).Unlikethepreviousworksthattrackfacialfeaturepointsindependentlyorbuildashapemodeltocap-turethevariationsoffaceshapeorappearanceregardlessofthefacialexpressionsandfaceposes,theproposedmodelcouldcapturethedistinctionsaswellasthevariationsoffaceshapesduetofacialexpressionandposechangeinauniﬁedframework.Speciﬁcally,weﬁrstconstructamodel1"
-25c108a56e4cb757b62911639a40e9caf07f1b4f,Recurrent Scale Approximation for Object Detection in CNN,"Recurrent Scale Approximation for Object Detection in CNN
-Yu Liu1,2, Hongyang Li2, Junjie Yan1, Fangyin Wei1, Xiaogang Wang2, Xiaoou Tang2
-Multimedia Laboratory at The Chinese University of Hong Kong
-SenseTime Group Limited"
 25e05a1ea19d5baf5e642c2a43cca19c5cbb60f8,Label Distribution Learning,"Label Distribution Learning
 Xin Geng*, Member, IEEE"
 2559b15f8d4a57694a0a33bdc4ac95c479a3c79a,Contextual Object Localization With Multiple Kernel Nearest Neighbor,"Contextual Object Localization With Multiple