A list of 100 things computer vision can see, eg:
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’
for i in {1..9};do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_0$i.MP4;done;for i in {10..20}; do wget http://visiond1.cs.umbc.edu/webpage/codedata/ADLdataset/ADL_videos/P_$i.MP4;done
The 27 attributes are:
| attribute | representation in file | label |
|---|---|---|
| gender | gender | male(1), female(2) |
| hair length | hair | short hair(1), long hair(2) |
| sleeve length | up | long sleeve(1), short sleeve(2) |
| length of lower-body clothing | down | long lower body clothing(1), short(2) |
| type of lower-body clothing | clothes | dress(1), pants(2) |
| wearing hat | hat | no(1), yes(2) |
| carrying backpack | backpack | no(1), yes(2) |
| carrying bag | bag | no(1), yes(2) |
| carrying handbag | handbag | no(1), yes(2) |
| age | age | young(1), teenager(2), adult(3), old(4) |
| 8 color of upper-body clothing | upblack, upwhite, upred, uppurple, upyellow, upgray, upblue, upgreen | no(1), yes(2) |
| 9 color of lower-body clothing | downblack, downwhite, downpink, downpurple, downyellow, downgray, downblue, downgreen,downbrown | no(1), yes(2) |
source: https://github.com/vana77/Market-1501_Attribute/blob/master/README.md
The 23 attributes are:
| attribute | representation in file | label |
|---|---|---|
| gender | gender | male(1), female(2) |
| length of upper-body clothing | top | short upper body clothing(1), long(2) |
| wearing boots | boots | no(1), yes(2) |
| wearing hat | hat | no(1), yes(2) |
| carrying backpack | backpack | no(1), yes(2) |
| carrying bag | bag | no(1), yes(2) |
| carrying handbag | handbag | no(1), yes(2) |
| color of shoes | shoes | dark(1), light(2) |
| 8 color of upper-body clothing | upblack, upwhite, upred, uppurple, upgray, upblue, upgreen, upbrown | no(1), yes(2) |
| 7 color of lower-body clothing | downblack, downwhite, downred, downgray, downblue, downgreen, downbrown | no(1), yes(2) |
source: https://github.com/vana77/DukeMTMC-attribute/blob/master/README.md
The joints and other keypoints (eyes, ears, nose, shoulders, elbows, wrists, hips, knees and ankles) The 3D pose inferred from the keypoints. Visibility boolean for each keypoint Region annotations (upper clothes, lower clothes, dress, socks, shoes, hands, gloves, neck, face, hair, hat, sunglasses, bag, occluder) Body type (male, female or child)
source: https://www2.eecs.berkeley.edu/Research/Projects/CS/vision/shape/h3d/
=INDEX(A2:A9,MATCH(datasets!D1,B2:B9,0)) =VLOOKUP(A2, datasets!A:J, 7, FALSE)
Right ankle Right knee Right hip Left hip Left knee Left ankle Right wrist Right elbow Right shoulder Left shoulder Left elbow Left wrist Neck Head top
source: http://web.archive.org/web/20170915023005/sam.johnson.io/research/lsp.html