---------------------------------------------------------------------- KU-POD dataset for Yeong Jun Koh and Chang-Su Kim, "Unsupervised Primary Object Discovery in Videos Based on Evolutionary Primary Object Modeling with Reliable Object Proposals" submitted to IEEE TIP If you have any comment, suggestion, or question, please contact Yeong Jun Koh (yjkoh@mcl.korea.ac.kr). ---------------------------------------------------------------------- KU-POD dataset ---------------------------------------------------------------------- KU-POD is composed of 83 videos: 9 from Segtrack v2, 37 from FBMS, and 37 from VSB100. A. Segtrack v2 [1] http://web.engr.oregonstate.edu/~lif/SegTrack2/dataset.html B. FBMS [2] http://lmb.informatik.uni-freiburg.de/resources/datasets/moseg.en.html C. VSB100 [3] http://lmb.informatik.uni-freiburg.de/resources/datasets/vsb.en.html See our project page for discovery results and ground-truth: https://mcl.korea.ac.kr/PrimaryObjectDiscovery ---------------------------------------------------------------------- Sequence List ---------------------------------------------------------------------- A. Segtrack v2 bird_of_paradise birdfall frog girl monkey monkeydog parachute soldier worm B. FBMS 1) Test set camel01 cars1 cars4 cats01 cats03 cats06 dogs01 dogs02 horses02 lion01 marple12 marple2 marple4 marple6 people03 people1 people2 rabbits04 tennis 2) Training set bear01 bear02 cars6 cars7 cars8 cats02 cats05 horses01 horses03 marple1 marple11 marple13 marple5 marple8 meerkats01 people05 rabbits01 rabbits05 C. VSB100 1) Test set animal_chase buck chameleons fish_underwater freight_train gokart harley_davidson horse_gate jungle_cat kim_yu_na koala nordic_skiing octopus palm_tree panda planet_earth_1 rock_climbing shark_attack snow_leopards snowboarding swimming yosemite 2) Training set alec_baldwin bowling car_jump drone gray_squirrel horse_riding lion lion2 rock_climbing sailing sea_snake sitting_dog swing tarantula trampoline ---------------------------------------------------------------------- Reference ---------------------------------------------------------------------- [1] F. Li, T. Kim, A. Humayun, D. Tsai, and J. Rehg, “Video segmentation by tracking many figure-ground segments,” in ICCV, 2013, pp. 2192– 2199. [2] T. Brox and J. Malik, “Object segmentation by long term analysis of point trajectories,” in ECCV, 2010, pp. 282–295. [3] F. Galasso, N. Nagaraja, T. Cardenas, T. Brox, and B. Schiele, “A unified video segmentation benchmark: Annotation, metrics and analysis,” in ICCV, 2013, pp. 3527–3534.