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authoradamhrv <adam@ahprojects.com>2019-04-17 22:46:34 +0200
committeradamhrv <adam@ahprojects.com>2019-04-17 22:46:34 +0200
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@@ -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