From 27340ac4cd43f8eec7414495b541a65566ae2656 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Tue, 8 Oct 2019 16:02:47 +0200 Subject: update site, white --- site/public/datasets/msceleb/index.html | 29 ++++++++++++++++++++--------- 1 file changed, 20 insertions(+), 9 deletions(-) (limited to 'site/public/datasets/msceleb/index.html') diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html index 42a44571..f0da450f 100644 --- a/site/public/datasets/msceleb/index.html +++ b/site/public/datasets/msceleb/index.html @@ -55,8 +55,8 @@
-
MS Celeb is a dataset of 10 million face images harvested from the Internet
The MS Celeb dataset includes 10 million images of 100,000 people and an additional target list of 1,000,000 individuals -

Microsoft Celeb Dataset (MS Celeb)

+
Example images forom the MS-Celeb-1M dataset

Microsoft Celeb Dataset (MS Celeb)

+

Update: In response to this report and an investigation by the Financial Times, Microsoft has terminated their MS-Celeb website https://msceleb.org.

Published
2016
@@ -78,7 +78,8 @@
Website
-

Microsoft Celeb (MS-Celeb-1M) is a dataset of 10 million face images harvested from the Internet for the purpose of developing face recognition technologies. According to Microsoft Research, who created and published the dataset in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals' biometric data to accelerate research into recognizing a larger target list of one million people "using all the possibly collected face images of this individual on the web as training data". 1

+
Press coverage
Financial Times, New York Times, BBC, Spiegel, Les Echos, La Stampa

Microsoft Celeb (MS-Celeb-1M) is a dataset of 10 million face images harvested from the Internet for the purpose of developing face recognition technologies.

+

According to Microsoft Research, who created and published the dataset in 2016, MS Celeb is the largest publicly available face recognition dataset in the world, containing over 10 million images of nearly 100,000 individuals. Microsoft's goal in building this dataset was to distribute an initial training dataset of 100,000 individuals' biometric data to accelerate research into recognizing a larger target list of one million people "using all the possibly collected face images of this individual on the web as training data". 1

While the majority of people in this dataset are American and British actors, the exploitative use of the term "celebrity" extends far beyond Hollywood. Many of the names in the MS Celeb face recognition dataset are merely people who must maintain an online presence for their professional lives: journalists, artists, musicians, activists, policy makers, writers, and academics. Many people in the target list are even vocal critics of the very technology Microsoft is using their name and biometric information to build. It includes digital rights activists like Jillian York; artists critical of surveillance including Trevor Paglen, Jill Magid, and Aram Bartholl; Intercept founders Laura Poitras, Jeremy Scahill, and Glenn Greenwald; Data and Society founder danah boyd; Shoshana Zuboff, author of Surveillance Capitalism; and even Julie Brill, the former FTC commissioner responsible for protecting consumer privacy.

Microsoft's 1 Million Target List

Microsoft Research distributed two main digital assets: a dataset of approximately 10,000,000 images of 100,000 individuals and a target list of exactly 1 million names. The 900,000 names without images are the target list, which is used to gather more images for each subject.

@@ -219,6 +220,8 @@

In 2017 Microsoft Research organized a face recognition competition at the International Conference on Computer Vision (ICCV), one of the top 2 computer vision conferences worldwide, where industry and academia used the MS Celeb dataset to compete for the highest performance scores. The 2017 winner was Beijing-based OrionStar Technology Co., Ltd.. In their press release, OrionStar boasted a 13% increase on the difficult set over last year's winner. The prior year's competitors included Beijing-based Faceall Technology Co., Ltd., a company providing face recognition for "smart city" applications.

Considering the multiple citations from commercial organizations (Canon, Hitachi, IBM, Megvii/Face++, Microsoft, Microsoft Asia, SenseTime, OrionStar, Faceall), military use (National University of Defense Technology in China), the proliferation of subset data (Racial Faces in the Wild), and the real-time visible proliferation via Academic Torrents it's fairly clear that Microsoft has lost control of their MS Celeb dataset and the biometric data of nearly 100,000 individuals.

To provide insight into where these 10 million faces images have traveled, over 100 research papers have been verified and geolocated to show who used the dataset and where they used it.

+

GDPR and MS-Celeb

+

[ in progress ]

Who used Microsoft Celeb?

@@ -240,10 +243,10 @@
-

Information Supply chain

+

Information Supply Chain

- To help understand how Microsoft Celeb has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Microsoft Celebrity Dataset was collected, verified, and geocoded to show the biometric trade routes of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how Microsoft Celeb has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Microsoft Celebrity Dataset was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

@@ -279,11 +282,19 @@

Supplementary Information

-
FAQs and Fact Check
+

Age and Gender Distribution

+
FAQs and Fact Check
+

Press Coverage

+

References

  • 1 abcMS-Celeb-1M: A Dataset and Benchmark for Large-Scale Face Recognition. Accessed April 18, 2019. http://web.archive.org/web/20190418151913/http://msceleb.org/
  • 2 aMurgia, Madhumita. Microsoft worked with Chinese military university on artificial intelligence. Financial Times. April 10, 2019. -- cgit v1.2.3-70-g09d2 From c574e09e73b90174d0c36caa1db5ad3b912ff466 Mon Sep 17 00:00:00 2001 From: adamhrv Date: Thu, 10 Oct 2019 12:22:12 +0200 Subject: update site theme, white --- TODO.md | 18 +- client/table/citations.table.js | 2 +- client/table/index.js | 3 +- client/table/tabulator.css | 32 +- package-lock.json | 1472 ++++++++++++++++++-- package.json | 3 +- site/assets/css/applets.css | 2 +- site/assets/css/css.css | 8 +- site/content/pages/datasets/duke_mtmc/index.md | 2 +- .../content/pages/datasets/helen/assets/gender.csv | 2 +- .../pages/datasets/megaface/assets/gender.csv | 6 +- site/includes/dashboard.html | 2 +- site/public/datasets/adience/index.html | 4 +- site/public/datasets/brainwash/index.html | 2 +- site/public/datasets/duke_mtmc/index.html | 6 +- site/public/datasets/helen/index.html | 2 +- site/public/datasets/ibm_dif/index.html | 4 +- site/public/datasets/ijb_c/index.html | 4 +- site/public/datasets/lfpw/index.html | 4 +- site/public/datasets/megaface/index.html | 7 +- site/public/datasets/msceleb/index.html | 2 +- site/public/datasets/oxford_town_centre/index.html | 2 +- site/public/datasets/pipa/index.html | 4 +- site/public/datasets/uccs/index.html | 2 +- site/public/datasets/who_goes_there/index.html | 4 +- 25 files changed, 1442 insertions(+), 157 deletions(-) (limited to 'site/public/datasets/msceleb/index.html') diff --git a/TODO.md b/TODO.md index da90ab57..69d73a00 100644 --- a/TODO.md +++ b/TODO.md @@ -2,21 +2,17 @@ ## Updates for NYT October 13/14 +### Dataset pages -### Charts - -- fix background hover on bar graph chart? remove extra black bg +- tabulator: remove hover effect (overriding css a:hover doesn't seem to fix it) +- bar chart, pie chart: possible to find better color scheme for white? The yellow is too light +- MegaFace dataset origin needs to be fixed (in the middle of the ocean now) ### CSS -- change tabulator to white/gry -- add a markdown parser? to handle a new update blurb at top of dataset pages. For now I used CSS selectors, but seems brittle -- can you check mobile css? my white-style edits might have broken - -### MegaFace Dataset - -- origin needs to be fixed (in the ocean) +- add a markdown parser to handle a new update blurb at top of dataset pages. For now I used CSS selectors, but seems brittle. Using this to call out the takedowns/important news +- can you check everything still works and looks good on mobile css? my white-style edits might have broken ### Homepage -- feel like we need a "face" +- feel like we need a "face lift" here. any ideas? \ No newline at end of file diff --git a/client/table/citations.table.js b/client/table/citations.table.js index c1c71906..45da5676 100644 --- a/client/table/citations.table.js +++ b/client/table/citations.table.js @@ -117,7 +117,7 @@ class CitationsTable extends Component { columns={citationsColumns} data={filteredCitations} options={{ - height: Math.max(104, Math.min(37 * formattedCitations.length + 29, 311)), + // height: Math.max(104, Math.min(30 * formattedCitations.length + 30, 1000)), layout: 'fitColumns', placeholder: formattedCitations.length ? '' : 'Nothing matches your query', }} diff --git a/client/table/index.js b/client/table/index.js index c741f33e..492a6ab3 100644 --- a/client/table/index.js +++ b/client/table/index.js @@ -1,5 +1,6 @@ import 'react-tabulator/lib/styles.css' -import 'react-tabulator/lib/css/tabulator_midnight.css' +//import 'react-tabulator/lib/css/tabulator_midnight.css' +import 'react-tabulator/lib/css/semantic-ui/tabulator_semantic-ui.css' import './tabulator.css' import CitationsTable from './citations.table' diff --git a/client/table/tabulator.css b/client/table/tabulator.css index 0d9e8ff1..a1504dd6 100644 --- a/client/table/tabulator.css +++ b/client/table/tabulator.css @@ -1,23 +1,27 @@ .tabulator { - border-left: 1px solid #333; - border-bottom: 1px solid #333; + /*border-left: 1px solid #333; + border-bottom: 1px solid #333;*/ font-size: 12px; } .tabulator-row.tabulator-row-odd { - background-color: #222; + background-color: #ddd; } .tabulator-row.tabulator-row-even { - background-color: #333; + background-color: #ebebeb; +} +.desktop .tabulator-row.tabulator-selectable.tabulator-row-odd:hover { + cursor: pointer ; + background-color: #ebebeb; } .desktop .tabulator-row.tabulator-selectable.tabulator-row-even:hover { - cursor: arrow; - background-color: #333; + cursor: pointer; + background-color: #ddd; } -.desktop .tabulator-row.tabulator-selectable.tabulator-row-odd:hover { - cursor: arrow; - background-color: #222; +.desktop .content .tabulator-row .tabulator-cell a{ + border-bottom: none; + text-decoration: underline; } -.tabulator-row .tabulator-cell { +/*.tabulator-row .tabulator-cell { border-right: 1px solid #444; padding: 8px; } @@ -33,7 +37,7 @@ .multi-value-formatter-content span { border: 0; padding: 0 5px 0 0; -} +}*/ .citationBrowser { } @@ -56,13 +60,15 @@ } .download { display: block; - font-size: 12px; + font-size: 11px; color: #333; cursor: pointer; background: #ddd; - padding: 5px 8px 5px 8px; + padding: 10px 14px; border-radius: 5px; transition: all 0.2s; + font-weight: 500; + text-transform: uppercase; border: 0 !important; } .content a.download { diff --git a/package-lock.json b/package-lock.json index 6920115d..ed66ddfb 100644 --- a/package-lock.json +++ b/package-lock.json @@ -211,6 +211,19 @@ } } }, + "@sindresorhus/is": { + "version": "0.14.0", + "resolved": "https://registry.npmjs.org/@sindresorhus/is/-/is-0.14.0.tgz", + "integrity": "sha512-9NET910DNaIPngYnLLPeg+Ogzqsi9uM4mSboU5y6p8S5DzMTVEsJZrawi+BoDNUVBa2DhJqQYUFvMDfgU062LQ==" + }, + "@szmarczak/http-timer": { + "version": "1.1.2", + "resolved": "https://registry.npmjs.org/@szmarczak/http-timer/-/http-timer-1.1.2.tgz", + "integrity": "sha512-XIB2XbzHTN6ieIjfIMV9hlVcfPU26s2vafYWQcZHWXHOxiaRZYEDKEwdl129Zyg50+foYV2jCgtrqSA6qNuNSA==", + "requires": { + "defer-to-connect": "^1.0.1" + } + }, "@types/node": { "version": "8.10.38", "resolved": "https://registry.npmjs.org/@types/node/-/node-8.10.38.tgz", @@ -238,6 +251,15 @@ "@types/react": "*" } }, + "JSONStream": { + "version": "1.3.5", + "resolved": "https://registry.npmjs.org/JSONStream/-/JSONStream-1.3.5.tgz", + "integrity": "sha512-E+iruNOY8VV9s4JEbe1aNEm6MiszPRr/UfcHMz0TQh1BXSxHK+ASV1R6W4HpjBhSeS+54PIsAMCBmwD06LLsqQ==", + "requires": { + "jsonparse": "^1.2.0", + "through": ">=2.2.7 <3" + } + }, "accepts": { "version": "1.3.5", "resolved": "https://registry.npmjs.org/accepts/-/accepts-1.3.5.tgz", @@ -288,6 +310,22 @@ } } }, + "agent-base": { + "version": "4.3.0", + "resolved": "https://registry.npmjs.org/agent-base/-/agent-base-4.3.0.tgz", + "integrity": "sha512-salcGninV0nPrwpGNn4VTXBb1SOuXQBiqbrNXoeizJsHrsL6ERFM2Ne3JUSBWRE6aeNJI2ROP/WEEIDUiDe3cg==", + "requires": { + "es6-promisify": "^5.0.0" + } + }, + "agentkeepalive": { + "version": "3.5.2", + "resolved": "https://registry.npmjs.org/agentkeepalive/-/agentkeepalive-3.5.2.tgz", + "integrity": "sha512-e0L/HNe6qkQ7H19kTlRRqUibEAwDK5AFk6y3PtMsuut2VAH6+Q4xZml1tNDJD7kSAyqmbG/K08K5WEJYtUrSlQ==", + "requires": { + "humanize-ms": "^1.2.1" + } + }, "ajv": { "version": "6.6.1", "resolved": "https://registry.npmjs.org/ajv/-/ajv-6.6.1.tgz", @@ -320,6 +358,39 @@ "repeat-string": "^1.5.2" } }, + "ansi-align": { + "version": "3.0.0", + "resolved": "https://registry.npmjs.org/ansi-align/-/ansi-align-3.0.0.tgz", + "integrity": "sha512-ZpClVKqXN3RGBmKibdfWzqCY4lnjEuoNzU5T0oEFpfd/z5qJHVarukridD4juLO2FXMiwUQxr9WqQtaYa8XRYw==", + "requires": { + "string-width": "^3.0.0" + }, + "dependencies": { + "ansi-regex": { + "version": "4.1.0", + "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-4.1.0.tgz", + "integrity": "sha512-1apePfXM1UOSqw0o9IiFAovVz9M5S1Dg+4TrDwfMewQ6p/rmMueb7tWZjQ1rx4Loy1ArBggoqGpfqqdI4rondg==" + }, + "string-width": { + "version": "3.1.0", + "resolved": "https://registry.npmjs.org/string-width/-/string-width-3.1.0.tgz", + "integrity": "sha512-vafcv6KjVZKSgz06oM/H6GDBrAtz8vdhQakGjFIvNrHA6y3HCF1CInLy+QLq8dTJPQ1b+KDUqDFctkdRW44e1w==", + "requires": { + "emoji-regex": "^7.0.1", + "is-fullwidth-code-point": "^2.0.0", + "strip-ansi": "^5.1.0" + } + }, + "strip-ansi": { + "version": "5.2.0", + "resolved": "https://registry.npmjs.org/strip-ansi/-/strip-ansi-5.2.0.tgz", + "integrity": "sha512-DuRs1gKbBqsMKIZlrffwlug8MHkcnpjs5VPmL1PAh+mA30U0DTotfDZ0d2UUsXpPmPmMMJ6W773MaA3J+lbiWA==", + "requires": { + "ansi-regex": "^4.1.0" + } + } + } + }, "ansi-colors": { "version": "3.2.3", "resolved": "https://registry.npmjs.org/ansi-colors/-/ansi-colors-3.2.3.tgz", @@ -341,14 +412,12 @@ "ansi-regex": { "version": "2.1.1", "resolved": "https://registry.npmjs.org/ansi-regex/-/ansi-regex-2.1.1.tgz", - "integrity": "sha1-w7M6te42DYbg5ijwRorn7yfWVN8=", - "dev": true + "integrity": "sha1-w7M6te42DYbg5ijwRorn7yfWVN8=" }, "ansi-styles": { "version": "2.2.1", "resolved": "https://registry.npmjs.org/ansi-styles/-/ansi-styles-2.2.1.tgz", - "integrity": "sha1-tDLdM1i2NM914eRmQ2gkBTPB3b4=", - "dev": true + "integrity": "sha1-tDLdM1i2NM914eRmQ2gkBTPB3b4=" }, "anymatch": { "version": "1.3.2", @@ -374,7 +443,6 @@ "version": "1.0.10", 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"https://registry.npmjs.org/brace-expansion/-/brace-expansion-1.1.11.tgz", @@ -1675,8 +1814,7 @@ "builtin-modules": { "version": "1.1.1", "resolved": "https://registry.npmjs.org/builtin-modules/-/builtin-modules-1.1.1.tgz", - "integrity": "sha1-Jw8HbFpywC9bZaR9+Uxf46J4iS8=", - "dev": true + "integrity": "sha1-Jw8HbFpywC9bZaR9+Uxf46J4iS8=" }, "builtin-status-codes": { "version": "3.0.0", @@ -1684,6 +1822,11 @@ "integrity": "sha1-hZgoeOIbmOHGZCXgPQF0eI9Wnug=", "dev": true }, + "builtins": { + "version": "1.0.3", + "resolved": "https://registry.npmjs.org/builtins/-/builtins-1.0.3.tgz", + "integrity": "sha1-y5T662HIaWRR2zZTThQi+U8K7og=" + }, "bytes": { "version": "3.0.0", "resolved": "https://registry.npmjs.org/bytes/-/bytes-3.0.0.tgz", @@ -1744,6 +1887,40 @@ } } }, + "cacheable-request": { + "version": "6.1.0", + "resolved": "https://registry.npmjs.org/cacheable-request/-/cacheable-request-6.1.0.tgz", + "integrity": 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"sha512-DpKm2Ui/xN7/HQKCtpZxoRWBhZ9Z0kqtygG8XCgNQ8ZlDnxuQmWhj566j8fN4Cu3/JmbhsDo7fcAJq4s9h27Ew==", - "dev": true, "requires": { "spdx-correct": "^3.0.0", "spdx-expression-parse": "^3.0.0" } }, + "validate-npm-package-name": { + "version": "3.0.0", + "resolved": "https://registry.npmjs.org/validate-npm-package-name/-/validate-npm-package-name-3.0.0.tgz", + "integrity": "sha1-X6kS2B630MdK/BQN5zF/DKffQ34=", + "requires": { + "builtins": "^1.0.3" + } + }, "value-equal": { "version": "0.4.0", "resolved": "https://registry.npmjs.org/value-equal/-/value-equal-0.4.0.tgz", @@ -10851,7 +12107,6 @@ "version": "1.3.1", "resolved": "https://registry.npmjs.org/which/-/which-1.3.1.tgz", "integrity": "sha512-HxJdYWq1MTIQbJ3nw0cqssHoTNU267KlrDuGZ1WYlxDStUtKUhOaJmh112/TZmHxxUfuJqPXSOm7tDyas0OSIQ==", - "dev": true, "requires": { "isexe": "^2.0.0" } @@ -10862,6 +12117,14 @@ "integrity": "sha1-2e8H3Od7mQK4o6j6SzHD4/fm6Ho=", "dev": true }, + "widest-line": { + "version": "2.0.1", + "resolved": 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"https://registry.npmjs.org/xml2js/-/xml2js-0.4.19.tgz", diff --git a/package.json b/package.json index 7f53f126..b2d1340a 100644 --- a/package.json +++ b/package.json @@ -44,6 +44,7 @@ "leaflet": "^1.3.4", "leaflet-arc": "^1.0.2", "node-fetch": "^2.2.0", + "npm-check-updates": "^3.1.24", "parse-csv": "^0.2.0", "preact": "^8.4.2", "preact-compat": "^3.18.4", @@ -63,7 +64,7 @@ "snapsvg": "^0.5.1", "store2": "^2.7.0", "svgtodatauri": "0.0.0", - "tabulator-tables": "^4.1.3", + "tabulator-tables": "^4.4.3", "three": "^0.100.0", "three-orbitcontrols": "^2.99.1", "three.meshline": "^1.1.0", diff --git a/site/assets/css/applets.css b/site/assets/css/applets.css index 245643f1..70d8f51f 100644 --- a/site/assets/css/applets.css +++ b/site/assets/css/applets.css @@ -9,7 +9,7 @@ min-height: 0; } .applet { - margin-bottom: 60px; + margin-bottom: 0px; transition: opacity 0.2s cubic-bezier(0,0,1,1); opacity: 0; } diff --git a/site/assets/css/css.css b/site/assets/css/css.css index ae22fa1a..89ac8616 100644 --- a/site/assets/css/css.css +++ b/site/assets/css/css.css @@ -385,14 +385,14 @@ section h1, section h2, section h3, section h4, section h5, section h6, section line-height:34px; } .content-dataset section:nth-child(4) p:nth-child(2){ - font-size:20px; + font-size:18px; line-height: 34px; color:#000; } .content-dataset section:nth-child(3) p:nth-child(2) { /* highlight news text */ /*font-style: italic;*/ - font-weight: 500; + font-weight: 400; color:#f00; } .content-dataset section:nth-child(3) p:nth-child(2) a{ @@ -713,7 +713,7 @@ section.fullwidth .image { text-align: center; font-size: 10pt; line-height: 14pt; - color: #555; + color: #333; max-width: 960px; margin: 10px auto 10px auto; font-family: 'Roboto'; @@ -1304,7 +1304,7 @@ a.footnote_shim { margin-right: 10px; } .content .backlinks a { - color: #ff8; + color: #333; font-size: 10px; text-decoration: none; border: 0; diff --git a/site/content/pages/datasets/duke_mtmc/index.md b/site/content/pages/datasets/duke_mtmc/index.md index cba08a3c..e6a77269 100644 --- a/site/content/pages/datasets/duke_mtmc/index.md +++ b/site/content/pages/datasets/duke_mtmc/index.md @@ -16,7 +16,7 @@ authors: Adam Harvey # Duke MTMC -*Update: In response to this report and an [investigation](https://www.ft.com/content/cf19b956-60a2-11e9-b285-3acd5d43599e) by the Financial Times, Duke University has terminated the Duke MTMC dataset.* +Update: In response to this report and an [investigation](https://www.ft.com/content/cf19b956-60a2-11e9-b285-3acd5d43599e) by the Financial Times, Duke University has terminated the Duke MTMC dataset. ### sidebar ### end sidebar diff --git a/site/content/pages/datasets/helen/assets/gender.csv b/site/content/pages/datasets/helen/assets/gender.csv index e51919bc..ef44b6bd 100644 --- a/site/content/pages/datasets/helen/assets/gender.csv +++ b/site/content/pages/datasets/helen/assets/gender.csv @@ -1,4 +1,4 @@ gender,faces Male,1118 Female,1184 -They,186 +Overlap,186 diff --git a/site/content/pages/datasets/megaface/assets/gender.csv b/site/content/pages/datasets/megaface/assets/gender.csv index a23e6548..05ba9e43 100644 --- a/site/content/pages/datasets/megaface/assets/gender.csv +++ b/site/content/pages/datasets/megaface/assets/gender.csv @@ -1,4 +1,4 @@ gender,faces -male,884043 -female,580747 -they,94990 +Male,884043 +Female,580747 +Overlap,94990 diff --git a/site/includes/dashboard.html b/site/includes/dashboard.html index 02d054b5..4c98189d 100644 --- a/site/includes/dashboard.html +++ b/site/includes/dashboard.html @@ -37,7 +37,7 @@
  • Commercial
  • Military / Government
-
Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
+
Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
diff --git a/site/public/datasets/adience/index.html b/site/public/datasets/adience/index.html index a03fb3c6..9f621441 100644 --- a/site/public/datasets/adience/index.html +++ b/site/public/datasets/adience/index.html @@ -99,7 +99,7 @@

Information Supply Chain

- To help understand how Adience Benchmark Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Adience Benchmark was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how Adience Benchmark Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Adience Benchmark was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

@@ -114,7 +114,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/brainwash/index.html b/site/public/datasets/brainwash/index.html index efd2f5a8..31390edf 100644 --- a/site/public/datasets/brainwash/index.html +++ b/site/public/datasets/brainwash/index.html @@ -124,7 +124,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/duke_mtmc/index.html b/site/public/datasets/duke_mtmc/index.html index 351606cb..e86afe63 100644 --- a/site/public/datasets/duke_mtmc/index.html +++ b/site/public/datasets/duke_mtmc/index.html @@ -56,7 +56,7 @@
    A still frame from the Duke MTMC (Multi-Target-Multi-Camera) CCTV dataset captured on Duke University campus in 2014. The dataset has now been terminated by the author in response to this report.

    Duke MTMC

    -

    Update: In response to this report and an investigation by the Financial Times, Duke University has terminated the Duke MTMC dataset.

    +

    Update: In response to this report and an investigation by the Financial Times, Duke University has terminated the Duke MTMC dataset.

    Published
    2016
    @@ -272,7 +272,7 @@

    Information Supply Chain

    - To help understand how Duke MTMC Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Duke Multi-Target, Multi-Camera Tracking Project was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how Duke MTMC Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Duke Multi-Target, Multi-Camera Tracking Project was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

    @@ -287,7 +287,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/helen/index.html b/site/public/datasets/helen/index.html index ffd432b9..08791d29 100644 --- a/site/public/datasets/helen/index.html +++ b/site/public/datasets/helen/index.html @@ -174,7 +174,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/ibm_dif/index.html b/site/public/datasets/ibm_dif/index.html index f9e7a91d..924194a7 100644 --- a/site/public/datasets/ibm_dif/index.html +++ b/site/public/datasets/ibm_dif/index.html @@ -90,7 +90,7 @@

    Information Supply Chain

    - To help understand how IBM Diversity in Faces has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Diversity in Faces Dataset was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how IBM Diversity in Faces has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Diversity in Faces Dataset was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

    @@ -105,7 +105,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/ijb_c/index.html b/site/public/datasets/ijb_c/index.html index 1795ccbd..05826c3f 100644 --- a/site/public/datasets/ijb_c/index.html +++ b/site/public/datasets/ijb_c/index.html @@ -149,7 +149,7 @@

    Information Supply Chain

    - To help understand how IJB-C has been used around the world by commercial, military, and academic organizations; existing publicly available research citing IARPA Janus Benchmark C was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how IJB-C has been used around the world by commercial, military, and academic organizations; existing publicly available research citing IARPA Janus Benchmark C was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

    @@ -164,7 +164,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/lfpw/index.html b/site/public/datasets/lfpw/index.html index 7cee2116..cc2a2c3f 100644 --- a/site/public/datasets/lfpw/index.html +++ b/site/public/datasets/lfpw/index.html @@ -99,7 +99,7 @@

    Information Supply Chain

    - To help understand how LFPW has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled Face Parts in the Wild was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how LFPW has been used around the world by commercial, military, and academic organizations; existing publicly available research citing Labeled Face Parts in the Wild was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

    @@ -114,7 +114,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/megaface/index.html b/site/public/datasets/megaface/index.html index 7ef1842f..d213293a 100644 --- a/site/public/datasets/megaface/index.html +++ b/site/public/datasets/megaface/index.html @@ -67,7 +67,10 @@
    672,057
    Purpose
    -
    face recognition
    +
    Face recognition
    +
    +
    Created by
    +
    Ira Kemelmacher-Shlizerman
    Website
    washington.edu
    @@ -129,7 +132,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/msceleb/index.html b/site/public/datasets/msceleb/index.html index f0da450f..a664e99f 100644 --- a/site/public/datasets/msceleb/index.html +++ b/site/public/datasets/msceleb/index.html @@ -261,7 +261,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/oxford_town_centre/index.html b/site/public/datasets/oxford_town_centre/index.html index 24a5623d..3a7eabf0 100644 --- a/site/public/datasets/oxford_town_centre/index.html +++ b/site/public/datasets/oxford_town_centre/index.html @@ -119,7 +119,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/pipa/index.html b/site/public/datasets/pipa/index.html index dfc54654..9c0a974a 100644 --- a/site/public/datasets/pipa/index.html +++ b/site/public/datasets/pipa/index.html @@ -99,7 +99,7 @@

    Information Supply Chain

    - To help understand how PIPA Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing People in Photo Albums Dataset was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how PIPA Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing People in Photo Albums Dataset was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

    @@ -114,7 +114,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/uccs/index.html b/site/public/datasets/uccs/index.html index c7816b1f..8cc11c90 100644 --- a/site/public/datasets/uccs/index.html +++ b/site/public/datasets/uccs/index.html @@ -126,7 +126,7 @@ Their setup made it impossible for students to know they were being photographed
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    diff --git a/site/public/datasets/who_goes_there/index.html b/site/public/datasets/who_goes_there/index.html index b57bf469..0d19da0b 100644 --- a/site/public/datasets/who_goes_there/index.html +++ b/site/public/datasets/who_goes_there/index.html @@ -81,7 +81,7 @@

    Information Supply Chain

    - To help understand how Who Goes There Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing WhoGoesThere was collected, verified, and geocoded to show the information supply chains of people appearing in the images. Click on the markers to reveal research projects at that location. + To help understand how Who Goes There Dataset has been used around the world by commercial, military, and academic organizations; existing publicly available research citing WhoGoesThere was collected, verified, and geocoded to show how AI training data has proliferated around the world. Click on the markers to reveal research projects at that location.

    @@ -96,7 +96,7 @@
  • Commercial
  • Military / Government
    • -
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated.
    +
    Citation data is collected using SemanticScholar.org then dataset usage verified and geolocated. Citations are used to provide overview of how and where images were used.
    -- cgit v1.2.3-70-g09d2