BelgiumTSC dataset is built for traffic sign classification purposes. Is is a subset of BelgiumTS dataset and contains cropped images around annotations...
urban, traffic, road, classification, sign, belgiumWordNet is a large lexical database of English. Nouns, verbs, adjectives and adverbs are grouped into sets of cognitive synonyms (synsets), each express...
language, category, classification, imagenet, hierarchyMIT traffic data set is for research on activity analysis and crowded scenes. It includes a traffic video sequence of 90 minutes long. It is recorded by...
trackingThe Microsoft Research Cambridge-12 Kinect gesture dataset consists of sequences of human movements, represented as body-part locations, and the associa...
gesture, recognition, human, action, kinectThe Colosseum and San Marco are two image datasets for dense multiview stereo reconstructions used for evaluating the visual photo realism. The datase...
urban, aerial, streetside, 3d reconstruction, photo-realism, flickr, landmark, sfmThis dataset is for people tracking in wide baseline camera networks and was designed as a contest at ICPR 2012. The contest consists of two challeng...
trajectory, pedestrian, occlusion, crowd, object tracking, overlap, aerial, object detectionThe Semantic Description of Human Activities (SDHA) was a contest at ICPR 2010. The contest is composed of three different types of activity recognit...
trajectory, pedestrian, occlusion, crowd, object tracking, overlap, aerial, object detectionThe NYU-Depth V2 data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microso...
semantic segmentation, kinect, label, reconstruction, depthThe NYU-Depth data set is comprised of video sequences from a variety of indoor scenes as recorded by both the RGB and Depth cameras from the Microsoft ...
semantic segmentation, kinect, label, reconstruction, depthMIL data sets used in our 2002 NIPS paper for Elepphant, Musk, TREC http://www.cs.cmu.edu/~juny/MILL/MIL-experiments.htm
classification, machine learning