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| author | Jules Laplace <julescarbon@gmail.com> | 2019-04-18 22:15:24 +0200 |
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| committer | Jules Laplace <julescarbon@gmail.com> | 2019-04-18 22:15:24 +0200 |
| commit | 9464a43a5f674cc2d0f9270b6fd51922ac0e69a1 (patch) | |
| tree | 74186284853aa22b3a99b90ea1d11b7154735103 /site/content/pages/research | |
| parent | 925af2f19ac7c513d7b1567ab0f48a73e8fb8f6e (diff) | |
| parent | 95302fe0c52a8aaecc40410cc9c76d258e708faa (diff) | |
Merge branch 'master' of github.com:adamhrv/megapixels_dev
Diffstat (limited to 'site/content/pages/research')
| -rw-r--r-- | site/content/pages/research/02_what_computers_can_see/index.md | 7 |
1 files changed, 7 insertions, 0 deletions
diff --git a/site/content/pages/research/02_what_computers_can_see/index.md b/site/content/pages/research/02_what_computers_can_see/index.md index 51621f46..faa4ab17 100644 --- a/site/content/pages/research/02_what_computers_can_see/index.md +++ b/site/content/pages/research/02_what_computers_can_see/index.md @@ -25,6 +25,13 @@ A list of 100 things computer vision can see, eg: - tired, drowsiness in car - affectiva: interest in product, intent to buy +## From SenseTime paper + +Exploring Disentangled Feature Representation Beyond Face Identification + +From https://arxiv.org/pdf/1804.03487.pdf +The attribute IDs from 1 to 40 corre-spond to: ‘5 o Clock Shadow’, ‘Arched Eyebrows’, ‘Attrac-tive’, ‘Bags Under Eyes’, ‘Bald’, ‘Bangs’, ‘Big Lips’, ‘BigNose’, ‘Black Hair’, ‘Blond Hair’, ‘Blurry’, ‘Brown Hair’,‘Bushy Eyebrows’, ‘Chubby’, ‘Double Chin’, ‘Eyeglasses’,‘Goatee’, ‘Gray Hair’, ‘Heavy Makeup’, ‘High Cheek-bones’, ‘Male’, ‘Mouth Slightly Open’, ‘Mustache’, ‘Nar-row Eyes’, ‘No Beard’, ‘Oval Face’, ‘Pale Skin’, ‘PointyNose’, ‘Receding Hairline’, ‘Rosy Cheeks’, ‘Sideburns’,‘Smiling’, ‘Straight Hair’, ‘Wavy Hair’, ‘Wearing Ear-rings’, ‘Wearing Hat’, ‘Wearing Lipstick’, ‘Wearing Neck-lace’, ‘Wearing Necktie’ and ‘Young’. It’ + ## From PubFig Dataset |