TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation
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1 TagProp: Discriminative Metric Learning in Nearest Neighbor Models for Image Auto-Annotation M. Guillaumin, T. Mensink, J. Verbeek and C. Schmid LEAR team, INRIA Rhône-Alpes, France Supplementary Material
2 Summary We first present qualitative results on all three data sets (Corel 5k, ESP-Game and IAPR TC12) for the task of keyword-based image retrieval in Chapter 1 and next for the task of image auto-annotation in Chapter 2. 1
3 Contents 1 Keyword-based Image Retrieval Corel Database Keyword based retrieval good results Keyword based retrieval mean results Keyword based retrieval bad results Multiword queries retrieval good results Multiword queries retrieval mean results Multiword queries retrieval bad results ESP-Game Database Keyword based retrieval good results Keyword based retrieval mean results Keyword based retrieval bad results IAPR Database Keyword based retrieval good results Keyword based retrieval mean results Keyword based retrieval bad results Image Annotation Corel Database Best Predictions Median Predictions Worst Predictions ESP-Game Database Best Predictions Median Predictions Worst Predictions IAPR Database Best Predictions Median Predictions Worst Predictions
4 Chapter 1 Keyword-based Image Retrieval In our paper we compare performance of keyword based retrieval, i.e. given a keyword or several, rank the images by relevance. In these sections we show some example queries from all three databases. We have restricted ourselves to keywords where at least 8 images should have been returned. Because we also show 8 images of each query, in the perfect case all shown images are correct. Images whom are wrongly assigned to a keyword are marked with a red border. For each of the databases we show examples where our performance is good, median and bad. These scores are based on the Break Even Point (BEP) precision evaluation. For each query we show: query BEP (nr. of relevant images). For the Corel database we also show multi-word queries. 3
5 1.1 Corel Database Keyword based retrieval good results tiger (10) pool (11) cat (11) tracks (11) pillar (9) mare (9) foals (9) 4
6 1.1.2 Keyword based retrieval mean results street (26) grass (51) sky (105) plants (15) garden (10) tree (93) field (17) 5
7 1.1.3 Keyword based retrieval bad results shore (8) rocks (22) clouds (26) close-up (10) window (8) hills (18) town (9) 6
8 1.1.4 Multiword queries retrieval good results cars, tracks (10) cat, tiger (10) stone, pillar (8) water, pool (10) horses, foals (9) horses, mare (9) train, locomotive (9) 7
9 1.1.5 Multiword queries retrieval mean results sky, jet, plane (12) buildings, street (15) bear, snow (11) water, people (20) mountain, sky (18) tree, grass (11) mountain, tree (11) 8
10 1.1.6 Multiword queries retrieval bad results tree, house (8) water, beach, people (8) water, bridge (11) sky, tree (26) sky, clouds (15) people, street (8) beach, sand (8) 9
11 1.2 ESP-Game Database Keyword based retrieval good results coin (27) money (25) chart (38) map (46) graph (33) necklace (15) sky (188) 10
12 1.2.2 Keyword based retrieval mean results castle (12) comic (12) globe (12) plant (48) road (30) singer (9) horse (37) 11
13 1.2.3 Keyword based retrieval bad results statue 8.33 (12) letter 7.69 (13) ear 7.14 (28) arm 5.56 (18) album 0.00 (12) guy 0.00 (13) ice 0.00 (8) 12
14 1.3 IAPR Database Keyword based retrieval good results court (18) tennis (17) racetrack (11) player (24) grandstand (26) cyclist (45) grave (10) 13
15 1.3.2 Keyword based retrieval mean results wood (46) sand (30) column (42) bay (31) woman (248) cliff (43) car (79) 14
16 1.3.3 Keyword based retrieval bad results shoe 9.09 (11) area 8.33 (12) body 8.33 (12) backpack 5.56 (18) balcony 0.00 (11) dog 0.00 (10) paving 0.00 (10) 15
17 Chapter 2 Image Annotation To illustrate the performance of our model on the image annotation task, we show word predictions for a selection of images of the three data sets. Each data set is presented in three sections: Best predictions, Median predictions, and Worst predictions. These sections also relate to the BEP scores of our predictions compared to the ground-truth annotations, but here these BEP scores are computed by ranking keywords for a given image. When ties between BEP scores are observed, the images with the largest annotation sizes are kept. For each image, we show its BEP score, its ground-truth annotations, and the predictions of our model. The ground-truth words are sorted with our model s output score (shown in brackets), and are bold when the word is correctly predicted by our model. Predictions are also sorted with respect to their scores, and are bold if they appear in the ground-truth. We show as many predicted words as there are words in the ground-truth annotation for an image. 16
18 2.1 Corel Database Best Predictions Image BEP, Ground Truth, Prediction Ground Truth: coral (1.00), ocean (1.00), reefs (1.00), fan (1.00), sea (0.99) Predictions: coral (1.00), ocean (1.00), reefs (1.00), fan (1.00), sea (0.99) Ground Truth: field (1.00), foals (1.00), mare (1.00), horses (1.00) Predictions: field (1.00), foals (1.00), mare (1.00), horses (1.00) Ground Truth: sun (1.00), sky (1.00), tree (1.00), clouds (0.99) Predictions: sun (1.00), sky (1.00), tree (1.00), clouds (0.99) Ground Truth: mosque (1.00), temple (1.00), stone (1.00), pillar (1.00) Predictions: mosque (1.00), temple (1.00), stone (1.00), pillar (1.00) Ground Truth: plane (1.00), jet (1.00), sky (1.00), smoke (0.99) Predictions: plane (1.00), jet (1.00), sky (1.00), smoke (0.99) Ground Truth: canyon (1.00), valley (1.00), sand (1.00), rocks (1.00) Predictions: canyon (1.00), valley (1.00), sand (1.00), rocks (1.00) Ground Truth: bengal (1.00), tiger (1.00), cat (1.00), forest (1.00) Predictions: bengal (1.00), tiger (1.00), cat (1.00), forest (1.00) Ground Truth: black (1.00), bear (1.00), river (1.00), water (1.00) Predictions: black (1.00), bear (1.00), river (1.00), water (1.00) 17
19 2.1.2 Median Predictions Image BEP, Ground Truth, Prediction Ground Truth: buildings (0.99), tree (0.98), hills (0.46), town (0.35) Predictions: village (1.00), buildings (0.99), house (0.99), tree (0.98) Ground Truth: relief (1.00), ruins (1.00), sculpture (0.76), stone (0.73) Predictions: relief (1.00), ruins (1.00), wall (1.00), costume (0.92) Ground Truth: light (1.00), buildings (1.00), city (0.72), street (0.56) Predictions: harbor (1.00), light (1.00), skyline (1.00), buildings (1.00) Ground Truth: clouds (1.00), sky (0.99), desert (0.93), church (0.17) Predictions: clouds (1.00), valley (0.99), sky (0.99), sand (0.97) Ground Truth: mountain (1.00), tree (0.99), sky (0.98), clouds (0.94) Predictions: hillside (1.00), mountain (1.00), valley (0.99), tree (0.99) Ground Truth: grass (0.98), tree (0.98), bush (0.54), truck (0.05) Predictions: flowers (1.00), grass (0.98), tree (0.98), moose (0.95) Ground Truth: herd (0.99), grass (0.98), tundra (0.96), caribou (0.13) Predictions: sky (0.99), herd (0.99), grass (0.98), hills (0.97) Ground Truth: mountain (1.00), grass (0.99), landscape (0.79), road (0.32) Predictions: hillside (1.00), mountain (1.00), bush (1.00), grass (0.99) 18
20 2.1.3 Worst Predictions Image BEP, Ground Truth, Prediction Ground Truth: tree (0.89), street (0.89), house (0.82), tower (0.79) Predictions: bridge (0.98), water (0.97), sky (0.95), people (0.94) Ground Truth: water (1.00), sky (1.00), house (0.54), bridge (0.43) Predictions: buildings (1.00), boats (1.00), courtyard (1.00), canal (1.00) Ground Truth: snow (0.86), field (0.52), elk (0.14), bulls (0.13) Predictions: ice (1.00), frost (1.00), water (0.99), prototype (0.96) Ground Truth: flowers (0.87), wall (0.52), gate (0.43), lawn (0.01) Predictions: window (0.97), tree (0.96), interior (0.92), leaf (0.92) Ground Truth: water (0.92), coast (0.81), bridge (0.80), hills (0.68) Predictions: valley (0.98), tree (0.98), mountain (0.96), sky (0.95) Ground Truth: beach (0.98), water (0.98), people (0.96), sand (0.86) Predictions: snow (0.99), polar (0.99), tracks (0.99), bear (0.99) Ground Truth: horizon (0.99), water (0.98), mountain (0.76), sunrise (0.08) Predictions: sun (1.00), clouds (1.00), city (1.00), sky (1.00) Ground Truth: buildings (0.77), house (0.53), village (0.22), hillside (0.12) Predictions: tree (0.99), kauai (0.91), rocks (0.89), grass (0.89) 19
21 2.2 ESP-Game Database Best Predictions Image BEP, Ground Truth, Prediction Ground Truth: coin (1.00), old (1.00), metal (1.00), money (1.00), silver (1.00), round (1.00), circle (1.00), head (1.00), face (0.99) Predictions: coin (1.00), old (1.00), metal (1.00), money (1.00), silver (1.00), round (1.00), circle (1.00), head (1.00), face (0.99) Ground Truth: book (1.00), glasses (1.00), shirt (1.00), hand (1.00), old (1.00), green (1.00), man (1.00) Predictions: book (1.00), glasses (1.00), shirt (1.00), hand (1.00), old (1.00), green (1.00), man (1.00) Ground Truth: snow (1.00), fence (1.00), sky (1.00), mountain (1.00), white (0.98), tree (0.96) Predictions: snow (1.00), fence (1.00), sky (1.00), mountain (1.00), white (0.98), tree (0.96) Ground Truth: ocean (1.00), cloud (1.00), sea (1.00), sky (1.00), water (1.00), blue (1.00) Predictions: ocean (1.00), cloud (1.00), sea (1.00), sky (1.00), water (1.00), blue (1.00) Ground Truth: grass (1.00), tree (0.99), house (0.99), green (0.99), sky (0.98) Predictions: grass (1.00), tree (0.99), house (0.99), green (0.99), sky (0.98) Ground Truth: silver (1.00), coin (1.00), old (1.00), money (1.00), boat (1.00) Predictions: silver (1.00), coin (1.00), old (1.00), money (1.00), boat (1.00) Ground Truth: pot (1.00), tree (1.00), plant (1.00), green (1.00), leaf (1.00) Predictions: pot (1.00), tree (1.00), plant (1.00), green (1.00), leaf (1.00) Ground Truth: window (1.00), computer (1.00), gray (1.00), screen (1.00), blue (0.96) Predictions: window (1.00), computer (1.00), gray (1.00), screen (1.00), blue (0.96) 20
22 2.2.2 Median Predictions Image BEP, Ground Truth, Prediction BEP: 40% Ground Truth: map (0.99), red (0.89), yellow (0.79), black (0.79), numbers (0.23) Predictions: map (0.99), white (0.97), red (0.89), chart (0.85), blue (0.85) BEP: 40% Ground Truth: tv (0.98), comic (0.94), show (0.93), blue (0.90), yellow (0.69) Predictions: tv (0.98), movie (0.98), man (0.96), red (0.95), comic (0.94) BEP: 40% Ground Truth: man (0.99), woman (0.98), white (0.80), dog (0.26), show (0.14) Predictions: man (0.99), people (0.99), woman (0.98), red (0.96), painting (0.93) BEP: 40% Ground Truth: wave (0.99), girl (0.99), flower (0.97), black (0.93), america (0.11) Predictions: people (1.00), woman (1.00), wave (0.99), group (0.99), girl (0.99) BEP: 40% Ground Truth: black (0.99), picture (0.97), people (0.97), painting (0.90), group (0.59) Predictions: old (1.00), black (0.99), gray (0.99), man (0.99), picture (0.97) BEP: 40% Ground Truth: drawing (1.00), cartoon (1.00), kid (0.75), dog (0.72), brown (0.54) Predictions: drawing (1.00), cartoon (1.00), child (0.96), red (0.94), white (0.89) BEP: 40% Ground Truth: hair (0.98), woman (0.98), blonde (0.73), yellow (0.51), legs (0.34) Predictions: hair (0.98), woman (0.98), man (0.98), music (0.97), black (0.95) BEP: 40% Ground Truth: girl (0.99), woman (0.98), black (0.86), dance (0.73), ball (0.30) Predictions: man (0.99), girl (0.99), woman (0.98), people (0.97), pink (0.90) 21
23 2.2.3 Worst Predictions Image BEP, Ground Truth, Prediction Ground Truth: woman (0.83), cover (0.60), movie (0.53), magazine (0.36), fly (0.17), film (0.13) Predictions: sky (0.97), red (0.97), man (0.88), white (0.87), water (0.85), green (0.84) Ground Truth: water (0.85), blue (0.84), sea (0.47), plane (0.31), boat (0.28), army (0.18), war (0.15) Predictions: man (0.97), green (0.92), wall (0.90), white (0.90), grass (0.89), sky (0.89), black (0.88) Ground Truth: white (0.89), water (0.46), room (0.26), fire (0.25), wall (0.24), house (0.22), smoke (0.11) Predictions: suit (1.00), man (1.00), tie (0.99), door (0.99), people (0.99), woman (0.98), group (0.98) Ground Truth: people (0.75), red (0.70), city (0.66), building (0.56), car (0.51), mountain (0.33), street (0.17) Predictions: green (0.99), forest (0.98), leaf (0.98), tree (0.97), flower (0.97), yellow (0.95), grass (0.95) Ground Truth: snow (0.86), people (0.80), red (0.72), tower (0.68), yellow (0.53), mountain (0.37), ice (0.30) Predictions: sky (0.99), blue (0.99), building (0.95), house (0.94), man (0.91), water (0.90), tree (0.89) Ground Truth: water (0.87), boat (0.79), house (0.75), woman (0.71), game (0.66), lady (0.29), logo (0.28) Predictions: man (0.95), sky (0.94), white (0.91), building (0.90), ship (0.90), people (0.89), black (0.89) Ground Truth: blue (0.79), car (0.61), light (0.58), store (0.47), building (0.37), sign (0.36), moon (0.12), web (0.11) Predictions: man (0.99), table (0.97), people (0.96), tree (0.91), white (0.90), woman (0.90), black (0.89), red (0.85) Ground Truth: wood (0.62), face (0.59), eye (0.58), statue (0.36), nose (0.29), gray (0.27), person (0.25), mouth (0.14) Predictions: man (0.98), red (0.96), people (0.95), woman (0.95), brown (0.92), white (0.88), hat (0.84), picture (0.83) 22
24 2.3 IAPR Database Best Predictions Image BEP, Ground Truth, Prediction Ground Truth: bike (1.00), country (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), hand (1.00), racing (1.00), road (1.00), side (1.00), desert (1.00), hill (1.00), landscape (1.00), sky (1.00) Predictions: bike (1.00), country (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), hand (1.00), racing (1.00), road (1.00), side (1.00), desert (1.00), hill (1.00), landscape (1.00), sky (1.00) Ground Truth: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), line (1.00), power (1.00), short (1.00), hand (1.00), road (1.00), bottle (1.00), car (1.00), sky (1.00) Predictions: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), line (1.00), power (1.00), short (1.00), hand (1.00), road (1.00), bottle (1.00), car (1.00), sky (1.00) Ground Truth: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), shrub (1.00), road (1.00), desert (1.00), cloud (1.00), mountain (1.00), sky (1.00) Predictions: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), shrub (1.00), road (1.00), desert (1.00), cloud (1.00), mountain (1.00), sky (1.00) Ground Truth: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), cliff (1.00), meadow (1.00), road (1.00), landscape (1.00), cloud (1.00), sky (1.00) Predictions: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), cliff (1.00), meadow (1.00), road (1.00), landscape (1.00), cloud (1.00), sky (1.00) Ground Truth: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), shrub (1.00), road (1.00), desert (1.00), cloud (1.00), mountain (1.00), sky (1.00) Predictions: bike (1.00), cycling (1.00), cyclist (1.00), helmet (1.00), jersey (1.00), short (1.00), shrub (1.00), road (1.00), desert (1.00), cloud (1.00), mountain (1.00), sky (1.00) Ground Truth: cycling (1.00), cyclist (1.00), jersey (1.00), helmet (1.00), bike (1.00), highway (1.00), country (1.00), short (1.00), hand (1.00), sand (1.00), side (1.00), bush (1.00) Predictions: cycling (1.00), cyclist (1.00), jersey (1.00), helmet (1.00), bike (1.00), highway (1.00), country (1.00), short (1.00), hand (1.00), sand (1.00), side (1.00), bush (1.00) Ground Truth: cycling (1.00), power (1.00), cyclist (1.00), pole (1.00), bike (1.00), helmet (1.00), jersey (1.00), short (1.00), sun (1.00), road (1.00), shrub (1.00), sky (0.99) Predictions: cycling (1.00), power (1.00), cyclist (1.00), pole (1.00), bike (1.00), helmet (1.00), jersey (1.00), short (1.00), sun (1.00), road (1.00), shrub (1.00), sky (0.99) Ground Truth: cycling (1.00), cyclist (1.00), sky (1.00), road (1.00), cloud (1.00), bike (1.00), helmet (1.00), jersey (1.00), shrub (1.00), desert (1.00), short (1.00), mountain (1.00) Predictions: cycling (1.00), cyclist (1.00), sky (1.00), road (1.00), cloud (1.00), bike (1.00), helmet (1.00), jersey (1.00), shrub (1.00), desert (1.00), short (1.00), mountain (1.00) 23
25 2.3.2 Median Predictions Image BEP, Ground Truth, Prediction Ground Truth: pullover (1.00), boy (1.00) Predictions: cap (1.00), pullover (1.00) Ground Truth: sky (0.99), terrain (0.03) Predictions: cloud (1.00), sky (0.99) Ground Truth: cloud (0.99), meadow (0.99) Predictions: horizon (0.99), cloud (0.99) Ground Truth: sky (1.00), forest (0.90) Predictions: sky (1.00), slope (1.00) Ground Truth: salt (1.00), lake (0.42) Predictions: salt (1.00), desert (1.00) Ground Truth: woman (0.97), desert (0.70) Predictions: rock (0.99), woman (0.97) Ground Truth: woman (1.00), stand (0.99) Predictions: carpet (1.00), woman (1.00) Ground Truth: front (0.98), building (0.58) Predictions: front (0.98), child (0.98) 24
26 2.3.3 Worst Predictions Image BEP, Ground Truth, Prediction Ground Truth: woman (0.81), man (0.69), penguin (0.64), people (0.64), hill (0.43), jacket (0.36), trouser (0.22) Predictions: llama (0.99), rock (0.95), meadow (0.95), cliff (0.92), mountain (0.89), slope (0.89), waterfall (0.88) Ground Truth: road (0.57), bike (0.46), cyclist (0.40), short (0.31), cycling (0.20), shoe (0.09), sock (0.02) Predictions: canyon (0.99), man (0.95), branch (0.94), rock (0.91), side (0.89), slope (0.88), woman (0.86) Ground Truth: hand (0.68), roof (0.58), dress (0.27), head (0.23), girl (0.23), hair (0.19), hut (0.16) Predictions: man (0.98), woman (0.97), wall (0.97), tourist (0.95), front (0.93), people (0.89), hall (0.86) Ground Truth: bed (0.80), window (0.69), lamp (0.68), curtain (0.61), bedside (0.52), room (0.44), side (0.41) Predictions: man (0.94), woman (0.92), front (0.90), reed (0.90), column (0.89), sky (0.88), roof (0.88) Ground Truth: racetrack (1.00), meadow (0.99), people (0.64), hand (0.23), tent (0.21), flag (0.17), lane (0.05) Predictions: grandstand (1.00), uniform (1.00), jersey (1.00), team (1.00), short (1.00), field (1.00), stadium (1.00) Ground Truth: tourist (0.94), front (0.94), brick (0.93), door (0.84), girl (0.68), boy (0.50), building (0.49) Predictions: wall (1.00), room (1.00), window (0.99), man (0.96), table (0.96), woman (0.96), chair (0.95) Ground Truth: bed (0.80), wood (0.42), room (0.41), lamp (0.38), table (0.33), night (0.17), clock (0.06), bedcover (0.06) Predictions: field (0.99), landscape (0.98), house (0.96), terrace (0.94), tree (0.94), mountain (0.94), slope (0.92), meadow (0.88) Ground Truth: lawn (0.76), chair (0.67), table (0.60), shade (0.42), sun (0.41), shore (0.33), lake (0.22), sign (0.18), cliff (0.17) Predictions: tree (1.00), garden (0.94), man (0.92), house (0.91), sky (0.89), woman (0.88), people (0.88), front (0.86), plant (0.82) 25
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