From 1369a597f2f564bf305e0918f91e2a96a4fded82 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 12:06:14 +0200 Subject: brainwash, example sidebar --- .../datasets/brainwash/assets/00818000_640x480.jpg | Bin 33112 -> 0 bytes .../datasets/brainwash/assets/background_540.jpg | Bin 83594 -> 0 bytes .../datasets/brainwash/assets/background_600.jpg | Bin 86425 -> 0 bytes .../brainwash/assets/brainwash_mean_overlay.jpg | Bin 0 -> 150399 bytes .../brainwash/assets/brainwash_mean_overlay_wm.jpg | Bin 0 -> 151713 bytes site/content/pages/datasets/brainwash/index.md | 41 ++++++++++++++++----- 6 files changed, 31 insertions(+), 10 deletions(-) delete mode 100644 site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg delete mode 100644 site/content/pages/datasets/brainwash/assets/background_540.jpg delete mode 100755 site/content/pages/datasets/brainwash/assets/background_600.jpg create mode 100755 site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg create mode 100755 site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg (limited to 'site/content/pages/datasets/brainwash') diff --git a/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg b/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg deleted file mode 100644 index 30c0fcb1..00000000 Binary files a/site/content/pages/datasets/brainwash/assets/00818000_640x480.jpg and /dev/null differ diff --git a/site/content/pages/datasets/brainwash/assets/background_540.jpg b/site/content/pages/datasets/brainwash/assets/background_540.jpg deleted file mode 100644 index 5c8c0ad4..00000000 Binary files a/site/content/pages/datasets/brainwash/assets/background_540.jpg and /dev/null differ diff --git a/site/content/pages/datasets/brainwash/assets/background_600.jpg b/site/content/pages/datasets/brainwash/assets/background_600.jpg deleted file mode 100755 index 8f2de697..00000000 Binary files a/site/content/pages/datasets/brainwash/assets/background_600.jpg and /dev/null differ diff --git a/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg new file mode 100755 index 00000000..2f5917e3 Binary files /dev/null and b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay.jpg differ diff --git a/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg new file mode 100755 index 00000000..790dbb79 Binary files /dev/null and b/site/content/pages/datasets/brainwash/assets/brainwash_mean_overlay_wm.jpg differ diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 0bf67455..d9bffb39 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -19,28 +19,24 @@ authors: Adam Harvey + Published: 2015 + Images: 11,918 + Faces: 91,146 -+ Created by: Stanford Department of Computer Science ++ Created by: Stanford University (US)
Max Planck Institute for Informatics (DE) + Funded by: Max Planck Center for Visual Computing and Communication -+ Location: Brainwash Cafe, San Franscisco -+ Purpose: Training face detection ++ Purpose: Face detection + Website: stanford.edu -+ Paper: End-to-End People Detection in Crowded Scenes -+ Explicit Consent: No ## Brainwash Dataset (PAGE UNDER DEVELOPMENT) -*Brainwash* is a face detection dataset created from the Brainwash Cafe's livecam footage including 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to develop face detection algorithms for the "challenging task of detecting people in crowded scenes" and tracking them. +*Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to train and validate algorithms for detecting people in crowded scenes. -Before closing in 2017, Brainwash Cafe was a "cafe and laundromat" located in San Francisco's SoMA district. The cafe published a publicy available livestream from the cafe with a view of the cash register, performance stage, and seating area. +Before closing in 2017, The Brainwash Cafe was a combination cafe, laundromat, and performance venue located in San Francisco's SoMA district. The images used for Brainwash dataset were captured on 3 days: October 27, November 13, and November 24 in 2014. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper]. -Since it's publication by Stanford in 2015, the Brainwash dataset has appeared in several notable research papers. In September 2016 four researchers from the National University of Defense Technology in Changsha, China used the Brainwash dataset for a research study on "people head detection in crowded scenes", concluding that their algorithm "achieves superior head detection performance on the crowded scenes dataset[^localized_region_context]". And again in 2017 three researchers at the National University of Defense Technology used Brainwash for a study on object detection noting "the data set used in our experiment is shown in Table 1, which includes one scene of the brainwash dataset[^replacement_algorithm]". +Brainwash is not a widely used dataset but since it's publication by Stanford in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on "people head detection in crowded scenes" [^localized_region_context] [^replacement_algorithm]. -![caption: An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)](assets/00425000_960.jpg) +![caption: The pixel-averaged image of all Brainwash dataset images is shown with 81,973 head annotations drawn from the Brainwash training partition. (c) Adam Harvey](assets/brainwash_mean_overlay.jpg) -![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) {% include 'chart.html' %} @@ -55,12 +51,37 @@ Add more analysis here {% include 'citations.html' %} +![caption: An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)](assets/00425000_960.jpg) + +![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) ### Additional Information - The dataset author spoke about his research at the CVPR conference in 2016 +To evaluate the performance of our approach, we collected a +large dataset of images from busy scenes using video footage available from public webcams. In +total, we collect 11917 images with 91146 labeled people. We extract images from video footage at +a fixed interval of 100 seconds to ensure a large variation in images. We allocate 1000 images for +testing and validation, and leave the remaining images for training, making sure that no temporal +overlaps exist between training and test splits. The resulting training set contains 82906 instances. +Test and validation sets contain 4922 and 3318 people instances respectively. Images were labeled +using Amazon Mechanical Turk by a handful of workers pre-selected through their performance on +an example task. We label each person’s head to avoid ambiguity in bounding box locations. The +annotator labels any person she is able to recognize, even if a substantial part of the person is not +visible. Images and annotations will be made available 1 . +Examples of collected images are shown in Fig. 6, and in the video included in the supplemental +material. Images in our dataset include challenges such as people at small scales, strong partial +occlusions, and a large variability in clothing and appearance. + +TODO + +- add bounding boxes to the header image +- remake montage with randomized images, with bboxes +- clean up intro text + + ### Footnotes [^readme]: "readme.txt" https://exhibits.stanford.edu/data/catalog/sx925dc9385. -- cgit v1.2.3-70-g09d2 From 1d261333895cb9305c73d02170e61c5100a39358 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Mon, 1 Apr 2019 12:49:57 +0200 Subject: add dataset size --- site/content/pages/datasets/brainwash/index.md | 38 +++++++------------------- 1 file changed, 10 insertions(+), 28 deletions(-) (limited to 'site/content/pages/datasets/brainwash') diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index d9bffb39..6d90e78f 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -2,8 +2,8 @@ status: published title: Brainwash -desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco -subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection algorithms +desc: Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014 +subdesc: The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms slug: brainwash cssclass: dataset image: assets/background.jpg @@ -21,19 +21,18 @@ authors: Adam Harvey + Faces: 91,146 + Created by: Stanford University (US)
Max Planck Institute for Informatics (DE) + Funded by: Max Planck Center for Visual Computing and Communication -+ Purpose: Face detection ++ Purpose: Head detection ++ Download Size: 4.1GB + Website: stanford.edu ## Brainwash Dataset -(PAGE UNDER DEVELOPMENT) +*Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe"[^readme] captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper]. -*Brainwash* is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe[^readme]". The images are used to train and validate algorithms for detecting people in crowded scenes. +Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance [^localized_region_context] [^replacement_algorithm]. -Before closing in 2017, The Brainwash Cafe was a combination cafe, laundromat, and performance venue located in San Francisco's SoMA district. The images used for Brainwash dataset were captured on 3 days: October 27, November 13, and November 24 in 2014. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper]. - -Brainwash is not a widely used dataset but since it's publication by Stanford in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on "people head detection in crowded scenes" [^localized_region_context] [^replacement_algorithm]. +If you happen to have been at Brainwash cafe in San Franscisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset. ![caption: The pixel-averaged image of all Brainwash dataset images is shown with 81,973 head annotations drawn from the Brainwash training partition. (c) Adam Harvey](assets/brainwash_mean_overlay.jpg) @@ -44,42 +43,25 @@ Brainwash is not a widely used dataset but since it's publication by Stanford in {% include 'map.html' %} -Add more analysis here - +{% include 'citations.html' %} {% include 'supplementary_header.html' %} -{% include 'citations.html' %} - ![caption: An sample image from the Brainwash dataset used for training face and head detection algorithms for surveillance. The datset contains about 12,000 images. License: Open Data Commons Public Domain Dedication (PDDL)](assets/00425000_960.jpg) ![caption: 49 of the 11,918 images included in the Brainwash dataset. License: Open Data Commons Public Domain Dedication (PDDL)](assets/brainwash_montage.jpg) -### Additional Information +#### Additional Resources - The dataset author spoke about his research at the CVPR conference in 2016 -To evaluate the performance of our approach, we collected a -large dataset of images from busy scenes using video footage available from public webcams. In -total, we collect 11917 images with 91146 labeled people. We extract images from video footage at -a fixed interval of 100 seconds to ensure a large variation in images. We allocate 1000 images for -testing and validation, and leave the remaining images for training, making sure that no temporal -overlaps exist between training and test splits. The resulting training set contains 82906 instances. -Test and validation sets contain 4922 and 3318 people instances respectively. Images were labeled -using Amazon Mechanical Turk by a handful of workers pre-selected through their performance on -an example task. We label each person’s head to avoid ambiguity in bounding box locations. The -annotator labels any person she is able to recognize, even if a substantial part of the person is not -visible. Images and annotations will be made available 1 . -Examples of collected images are shown in Fig. 6, and in the video included in the supplemental -material. Images in our dataset include challenges such as people at small scales, strong partial -occlusions, and a large variability in clothing and appearance. - TODO - add bounding boxes to the header image - remake montage with randomized images, with bboxes - clean up intro text +- verify quote citations ### Footnotes -- cgit v1.2.3-70-g09d2 From b8f5c87e823d0b68d5e30f8de453ba90dcadc241 Mon Sep 17 00:00:00 2001 From: Jules Laplace Date: Tue, 2 Apr 2019 14:38:27 +0200 Subject: sidebar from spreadsheet --- megapixels/app/site/loader.py | 38 ++++++++++++++++++++++ megapixels/app/site/parser.py | 11 +------ site/assets/css/css.css | 11 +------ site/content/pages/datasets/brainwash/index.md | 11 +------ site/includes/sidebar.html | 6 ++++ .../datasets/50_people_one_question/index.html | 4 +-- site/public/datasets/brainwash/index.html | 24 ++++++++++++-- site/public/datasets/celeba/index.html | 4 +-- site/public/datasets/cofw/index.html | 4 +-- site/public/datasets/duke_mtmc/index.html | 4 +-- site/public/datasets/facebook/index.html | 3 +- site/public/datasets/hrt_transgender/index.html | 4 +-- site/public/datasets/lfw/index.html | 4 +-- site/public/datasets/market_1501/index.html | 4 +-- site/public/datasets/msceleb/index.html | 4 +-- site/public/datasets/pipa/index.html | 4 +-- site/public/datasets/uccs/index.html | 4 +-- site/public/datasets/viper/index.html | 4 +-- site/public/research/index.html | 18 ++++++++-- 19 files changed, 109 insertions(+), 57 deletions(-) create mode 100644 site/includes/sidebar.html (limited to 'site/content/pages/datasets/brainwash') diff --git a/megapixels/app/site/loader.py b/megapixels/app/site/loader.py index 779f68ba..701c78b2 100644 --- a/megapixels/app/site/loader.py +++ b/megapixels/app/site/loader.py @@ -5,6 +5,9 @@ import glob import app.settings.app_cfg as cfg from app.utils.file_utils import load_json +import app.utils.sheet_utils as sheet + +sidebar = sheet.fetch_google_lookup("sidebar", item_key="key") def read_metadata(fn): """ @@ -20,6 +23,12 @@ def read_metadata(fn): sections = data.split("\n\n") return parse_metadata(fn, sections) +def domainFromUrl(url): + domain = url.split('/')[2].split('.') + if len(domain) > 2 and len(domain[-2]) == 2: + return ".".join(domain[-3:]) + return ".".join(domain[-2:]) + default_metadata = { 'status': 'published', @@ -33,6 +42,18 @@ default_metadata = { 'tagline': '', } +sidebar_order = [ + { 'key': 'published', 'title': 'Published' }, + { 'key': 'images', 'title': 'Images' }, + { 'key': 'videos', 'title': 'Videos' }, + { 'key': 'identities', 'title': 'Identities' }, + { 'key': 'purpose', 'title': 'Purpose' }, + { 'key': 'created_by', 'title': 'Created by' }, + { 'key': 'funded_by_short', 'title': 'Funded by' }, + { 'key': 'size_gb', 'title': 'Download Size' }, + { 'key': 'website', 'title': 'Website' }, +] + def parse_metadata(fn, sections): """ parse the metadata headers in a markdown file @@ -87,8 +108,25 @@ def parse_metadata(fn, sections): print("Bad metadata? {}".format(dataset_path)) elif 'datasets' in fn: print("/!\\ {} does not exist!".format(dataset_path)) + + if metadata['slug'] in sidebar: + sidebar_row = sidebar[metadata['slug']] + if sidebar_row: + metadata['sidebar'] = [] + for item in sidebar_order: + key = item['key'] + value = sidebar_row[key] + if value: + value = value.replace(' - ', ' – ') + if key == 'size_gb': + value += ' GB' + if key == 'website': + value = "" + domainFromUrl(value) + "" + metadata['sidebar'].append({ 'value': value, 'title': item['title'], }) + if 'meta' not in metadata or not metadata['meta']: # dude metadata['meta'] = {} + metadata['sidebar'] = [] return metadata, valid_sections diff --git a/megapixels/app/site/parser.py b/megapixels/app/site/parser.py index 06c45f41..dc2a09f2 100644 --- a/megapixels/app/site/parser.py +++ b/megapixels/app/site/parser.py @@ -55,7 +55,7 @@ def parse_markdown(metadata, sections, s3_path, skip_h1=False): elif '### statistics' in section.lower() or '### sidebar' in section.lower(): if len(current_group): groups.append(format_section(current_group, s3_path)) - current_group = [] + current_group = [format_include("{% include 'sidebar.html' %}", metadata)] if 'sidebar' not in section.lower(): current_group.append(section) in_stats = True @@ -267,15 +267,6 @@ def format_include(section, metadata): include_fn = section.strip().strip('\n').strip().strip('{%').strip().strip('%}').strip() include_fn = include_fn.strip('include').strip().strip('"').strip().strip("'").strip() return includes_env.get_template(include_fn).render(metadata=metadata) - # include_dir = cfg.DIR_SITE_INCLUDES - # try: - # includes_env.get_template(fp_html) - # with open(join(include_dir, fp_html), 'r') as fp: - # html = fp.read().replace('\n', '') - # return html - # except Exception as e: - # print(f'Error parsing include: {e}') - # return '' def format_applet(section, s3_path): """ diff --git a/site/assets/css/css.css b/site/assets/css/css.css index 0ee8a4f3..30663ef7 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -1,4 +1,4 @@ -da* { box-sizing: border-box; outline: 0; } +* { box-sizing: border-box; outline: 0; } html, body { margin: 0; padding: 0; @@ -278,11 +278,8 @@ p.subp{ color: #ccc; margin-bottom: 20px; font-family: 'Roboto', sans-serif; -} -.meta > div { margin-right: 20px; line-height: 17px - /*font-size:11px;*/ } .meta .gray { font-size: 9pt; @@ -316,12 +313,6 @@ p.subp{ .left-sidebar .meta, .right-sidebar .meta { flex-direction: column; } -.right-sidebar .meta > div { - margin-bottom: 10px; -} -.left-sidebar .meta > div { - margin-bottom: 15px; -} .right-sidebar ul { margin-bottom: 10px; color: #aaa; diff --git a/site/content/pages/datasets/brainwash/index.md b/site/content/pages/datasets/brainwash/index.md index 6d90e78f..db88d949 100644 --- a/site/content/pages/datasets/brainwash/index.md +++ b/site/content/pages/datasets/brainwash/index.md @@ -15,16 +15,7 @@ authors: Adam Harvey ------------ ### sidebar - -+ Published: 2015 -+ Images: 11,918 -+ Faces: 91,146 -+ Created by: Stanford University (US)
Max Planck Institute for Informatics (DE) -+ Funded by: Max Planck Center for Visual Computing and Communication -+ Purpose: Head detection -+ Download Size: 4.1GB -+ Website: stanford.edu - +### end sidebar ## Brainwash Dataset diff --git a/site/includes/sidebar.html b/site/includes/sidebar.html new file mode 100644 index 00000000..0f7d2dad --- /dev/null +++ b/site/includes/sidebar.html @@ -0,0 +1,6 @@ +{% for item in metadata.sidebar %} +
+
{{ item.title }}
+
{{ item.value }}
+
+{% endfor %} \ No newline at end of file diff --git a/site/public/datasets/50_people_one_question/index.html b/site/public/datasets/50_people_one_question/index.html index 540e2d0d..1b03fc7e 100644 --- a/site/public/datasets/50_people_one_question/index.html +++ b/site/public/datasets/50_people_one_question/index.html @@ -27,7 +27,8 @@
People One Question is a dataset of people from an online video series on YouTube and Vimeo used for building facial recogntion algorithms
People One Question dataset includes ... -
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

50 People 1 Question

+

{% include 'sidebar.html' %}

+
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

50 People 1 Question

(PAGE UNDER DEVELOPMENT)

At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

@@ -71,7 +72,6 @@
-->
-
diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index 5e8f3a4c..c0830a96 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -27,7 +27,28 @@
Brainwash is a dataset of webcam images taken from the Brainwash Cafe in San Francisco in 2014
The Brainwash dataset includes 11,918 images of "everyday life of a busy downtown cafe" and is used for training head detection surveillance algorithms -
Published
2015
Images
11,918
Faces
91,146
Created by
Stanford University (US)
Max Planck Institute for Informatics (DE)
Funded by
Max Planck Center for Visual Computing and Communication
Purpose
Head detection
Download Size
4.1GB

Brainwash Dataset

+
+
Published
+
2015
+
+
Images
+
11,917
+
+
Purpose
+
Head detection
+
+
Created by
+
Stanford University (US), Max Planck Institute for Informatics (DE)
+
+
Funded by
+
Max Planck Center for Visual Computing and Communication
+
+
Download Size
+
4.1 GB
+
+
Website
+ +

Brainwash Dataset

Brainwash is a head detection dataset created from San Francisco's Brainwash Cafe livecam footage. It includes 11,918 images of "everyday life of a busy downtown cafe" 1 captured at 100 second intervals throught the entire day. Brainwash dataset was captured during 3 days in 2014: October 27, November 13, and November 24. According the author's reserach paper introducing the dataset, the images were acquired with the help of Angelcam.com [cite orig paper].

Brainwash is not a widely used dataset but since its publication by Stanford University in 2015, it has notably appeared in several research papers from the National University of Defense Technology in Changsha, China. In 2016 and in 2017 researchers there conducted studies on detecting people's heads in crowded scenes for the purpose of surveillance 2 3.

If you happen to have been at Brainwash cafe in San Franscisco at any time on October 26, November 13, or November 24 in 2014 you are most likely included in the Brainwash dataset.

@@ -94,7 +115,6 @@
-
diff --git a/site/public/datasets/celeba/index.html b/site/public/datasets/celeba/index.html index f1ee0c22..ef7a3b27 100644 --- a/site/public/datasets/celeba/index.html +++ b/site/public/datasets/celeba/index.html @@ -27,7 +27,8 @@
CelebA is a dataset of people...
CelebA includes... -
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

CelebA

+

{% include 'sidebar.html' %}

+
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

CelebA

(PAGE UNDER DEVELOPMENT)

At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

@@ -71,7 +72,6 @@
-->
-
diff --git a/site/public/datasets/cofw/index.html b/site/public/datasets/cofw/index.html index 1f5aa315..3520aaa2 100644 --- a/site/public/datasets/cofw/index.html +++ b/site/public/datasets/cofw/index.html @@ -26,7 +26,8 @@
-
Years
1993-1996
Images
14,126
Identities
1,199
Origin
Web Searches
Funded by
ODNI, IARPA, Microsoft

Caltech Occluded Faces in the Wild

+

{% include 'sidebar.html' %}

+
Years
1993-1996
Images
14,126
Identities
1,199
Origin
Web Searches
Funded by
ODNI, IARPA, Microsoft

Caltech Occluded Faces in the Wild

(PAGE UNDER DEVELOPMENT)

COFW is "is designed to benchmark face landmark algorithms in realistic conditions, which include heavy occlusions and large shape variations" [Robust face landmark estimation under occlusion].

RESEARCH below this line

@@ -81,7 +82,6 @@ To increase the number of training images, and since COFW has the exact same la
-->
-
diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index 83050506..c3e84053 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -27,7 +27,8 @@
Duke MTMC is a dataset of surveillance camera footage of students on Duke University campus
Duke MTMC contains over 2 million video frames and 2,000 unique identities collected from 8 HD cameras at Duke University campus in March 2014 -
Created
2014
Identities
Over 2,700
Used for
Face recognition, person re-identification
Created by
Computer Science Department, Duke University, Durham, US
Website

Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)

+

{% include 'sidebar.html' %}

+
Created
2014
Identities
Over 2,700
Used for
Face recognition, person re-identification
Created by
Computer Science Department, Duke University, Durham, US
Website

Duke Multi-Target, Multi-Camera Tracking Dataset (Duke MTMC)

[ PAGE UNDER DEVELOPMENT ]

Duke MTMC is a dataset of video recorded on Duke University campus during for the purpose of training, evaluating, and improving multi-target multi-camera tracking. The videos were recorded during February and March 2014 and cinclude

Includes a total of 888.8 minutes of video (ind. verified)

@@ -89,7 +90,6 @@
-
diff --git a/site/public/datasets/facebook/index.html b/site/public/datasets/facebook/index.html index 7fb1901a..e9adb3f2 100644 --- a/site/public/datasets/facebook/index.html +++ b/site/public/datasets/facebook/index.html @@ -27,7 +27,8 @@
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Statistics

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{% include 'sidebar.html' %}

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Statistics

Years
2002-2004
Images
13,233
Identities
5,749
Origin
Yahoo News Images
Funding
(Possibly, partially CIA)

Ignore content below these lines

  • Tool to create face datasets from Facebook https://github.com/ankitaggarwal011/FaceGrab
    • diff --git a/site/public/datasets/hrt_transgender/index.html b/site/public/datasets/hrt_transgender/index.html index 528d1c3d..3215fb5d 100644 --- a/site/public/datasets/hrt_transgender/index.html +++ b/site/public/datasets/hrt_transgender/index.html @@ -27,7 +27,8 @@
    TBD
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    TBD
    Images
    TBD

    HRT Transgender Dataset

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HRT Transgender Dataset

Who used HRT Transgender?

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diff --git a/site/public/datasets/lfw/index.html b/site/public/datasets/lfw/index.html index 5f076fc7..562169e4 100644 --- a/site/public/datasets/lfw/index.html +++ b/site/public/datasets/lfw/index.html @@ -27,7 +27,8 @@
Labeled Faces in The Wild (LFW) is the first facial recognition dataset created entirely from online photos
It includes 13,456 images of 4,432 people's images copied from the Internet during 2002-2004 and is the most frequently used dataset in the world for benchmarking face recognition algorithms. -
Created
2002 – 2004
Images
13,233
Identities
5,749
Origin
Yahoo! News Images
Used by
Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA
Website
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{% include 'sidebar.html' %}

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Created
2002 – 2004
Images
13,233
Identities
5,749
Origin
Yahoo! News Images
Used by
Facebook, Google, Microsoft, Baidu, Tencent, SenseTime, Face++, CIA, NSA, IARPA
Website
  • There are about 3 men for every 1 woman in the LFW dataset 1
  • The person with the most images is George W. Bush with 530
  • There are about 3 George W. Bush's for every 1 Tony Blair
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diff --git a/site/public/datasets/market_1501/index.html b/site/public/datasets/market_1501/index.html index 951646e3..7d9f87f6 100644 --- a/site/public/datasets/market_1501/index.html +++ b/site/public/datasets/market_1501/index.html @@ -27,7 +27,8 @@
Market-1501 is a dataset is collection of CCTV footage from ...
The Market-1501 dataset includes ... -
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

Market-1501 ...

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TBD
Published
TBD
Images
TBD
Faces
TBD

Market-1501 ...

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diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html index 9a671c8e..ecab4c3a 100644 --- a/site/public/datasets/msceleb/index.html +++ b/site/public/datasets/msceleb/index.html @@ -27,7 +27,8 @@
MS Celeb is a dataset of web images used for training and evaluating face recognition algorithms
The MS Celeb dataset includes over 10,000,000 images and 93,000 identities of semi-public figures collected using the Bing search engine -
Published
TBD
Images
TBD
Faces
TBD
Created by
TBD

Microsoft Celeb Dataset (MS Celeb)

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Published
TBD
Images
TBD
Faces
TBD
Created by
TBD

Microsoft Celeb Dataset (MS Celeb)

(PAGE UNDER DEVELOPMENT)

At vero eos et accusamus et iusto odio dignissimos ducimus, qui blanditiis praesentium voluptatum deleniti atque corrupti, quos dolores et quas molestias excepturi sint, obcaecati cupiditate non-provident, similique sunt in culpa, qui officia deserunt mollitia animi, id est laborum et dolorum fuga. Et harum quidem rerum facilis est et expedita distinctio.

Nam libero tempore, cum soluta nobis est eligendi optio, cumque nihil impedit, quo minus id, quod maxime placeat, facere possimus, omnis voluptas assumenda est, omnis dolor repellendus. Temporibus autem quibusdam et aut officiis debitis aut rerum necessitatibus saepe eveniet, ut et voluptates repudiandae sint et molestiae non-recusandae. Itaque earum rerum hic tenetur a sapiente delectus, ut aut reiciendis voluptatibus maiores alias consequatur aut perferendis doloribus asperiores repellat

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Add more analysis here

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diff --git a/site/public/datasets/pipa/index.html b/site/public/datasets/pipa/index.html index fe6a4742..ff4302eb 100644 --- a/site/public/datasets/pipa/index.html +++ b/site/public/datasets/pipa/index.html @@ -27,7 +27,8 @@
is a dataset...
PIPA subdescription -
Collected
TBD
Published
TBD
Images
TBD
Faces
TBD

Dataset Title TBD

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TBD
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Faces
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Dataset Title TBD

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diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index 10b7603e..0925763b 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -27,7 +27,8 @@
Unconstrained College Students (UCCS) is a dataset of long-range surveillance photos of students taken without their knowledge
The UCCS dataset includes 16,149 images and 1,732 identities of students at University of Colorado Colorado Springs campus and is used for face recognition and face detection -
Published
2018
Images
16,149
Identities
1,732
Used for
Face recognition, face detection
Created by
Unviversity of Colorado Colorado Springs (US)
Funded by
ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR

Unconstrained College Students ...

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{% include 'sidebar.html' %}

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Published
2018
Images
16,149
Identities
1,732
Used for
Face recognition, face detection
Created by
Unviversity of Colorado Colorado Springs (US)
Funded by
ODNI, IARPA, ONR MURI, Amry SBIR, SOCOM SBIR

Unconstrained College Students ...

(PAGE UNDER DEVELOPMENT)

The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey
The pixel-average of all Uconstrained College Students images is shown with all 51,838 face annotations. (c) Adam Harvey
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diff --git a/site/public/datasets/viper/index.html b/site/public/datasets/viper/index.html index cc4272c8..b838c2b9 100644 --- a/site/public/datasets/viper/index.html +++ b/site/public/datasets/viper/index.html @@ -27,7 +27,8 @@
VIPeR is a person re-identification dataset of images captured at UC Santa Cruz in 2007
VIPeR contains 1,264 images and 632 persons on the UC Santa Cruz campus and is used to train person re-identification algorithms for surveillance -
Published
2007
Images
1,264
Persons
632
Created by
UC Santa Cruz

VIPeR Dataset

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{% include 'sidebar.html' %}

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Published
2007
Images
1,264
Persons
632
Created by
UC Santa Cruz

VIPeR Dataset

(PAGE UNDER DEVELOPMENT)

VIPeR (Viewpoint Invariant Pedestrian Recognition) is a dataset of pedestrian images captured at University of California Santa Cruz in 2007. Accoriding to the reserachers 2 "cameras were placed in different locations in an academic setting and subjects were notified of the presence of cameras, but were not coached or instructed in any way."

VIPeR is amongst the most widely used publicly available person re-identification datasets. In 2017 the VIPeR dataset was combined into a larger person re-identification created by the Chinese University of Hong Kong called PETA (PEdesTrian Attribute).

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diff --git a/site/public/research/index.html b/site/public/research/index.html index 303732f8..0ef57043 100644 --- a/site/public/research/index.html +++ b/site/public/research/index.html @@ -26,8 +26,22 @@
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Research Blog

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Research

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Posted
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2018-12-15
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By
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Adam Harvey
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