This website provides a list of frequently used computer vision datasets. Wait, there is more!
There is also a description containing common problems, pitfalls and characteristics and now a searchable TAG cloud.
Plus, this is open for crowd editing (if you pass the ultimate turing test)! - Questions? yacvid [at] hayko [dot] at
Content, Design and Idea © by Hayko Riemenschneider, 2011-2016. Texts and Images are subject of copyright by the respective authors.
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«showing 615 tags of 615 total tags for 427 datasets (1.44) »
|386||Utrecht University, ShakeFive2||ShakeFive2 A collection of 8 dyadic human interactions with accompanying skeleton metadata. The metadata is frame based xml data containing the skeleton join...||human interaction Kinect video||link||2017-06-26||149|
|367||NUS Multi-Sensor Presentation (NUSMSP) Dataset||This dataset consist 51 oral presentation recorded with 2 ambient visual sensor (web-cam), 3 First Person View (FPV) cameras (1 on presenter and 2 on randomly c...||multi-sensor presentation analysis video kinect quality||link||2017-09-12||265|
|308||TST Intake Monitoring dataBase||t is composed of food intake movements, recorded with Kinect V1 (320?40 depth frame resolution), simulated by 35 volunteers for a total of 48 tests. The device ...||human food intake monitoring behavior kinect pointcloud tracking age groundtruth||link||2018-01-06||587|
|305||SPHERE human skeleton movements||The SPHERE human skeleton movements dataset was created using a Kinect camera, that measures distances and provides a depth map of the scene instead of the clas...||human action behavior motion movement video skeleton depth kinect||link||2016-03-24||828|
|276||TST TUG (Timed Up and Go)||The TUG (Timed Up and Go test) dataset consists of actions performed three times by 20 volunteers. The people involved in the test are aged between 22 and 39, w...||action recognition time kinect wearable accelerometer human video||link||2015-05-02||662|
|275||TST fall detection||It is composed of ADL (activity daily living) and fall actions simulated by 11 volunteers. The people involved in the test are aged between 22 and 39, with diff...||action recognition detection depth kinect wearable accelerometer human video||link||2017-03-14||1006|
|271||Labeling in 3D Scenes||This dataset package contains the software and data used for Detection-based Object Labeling on the RGB-D Scenes Dataset as implemented in the paper: Detecti...||3d kinect reconstruction indoor depth object recognition||link||2015-03-16||861|
|270||B3DO: Berkeley 3D Object Dataset||For the first few decades of the fields existence, computer vision has been focused on algorithmic, logical approaches to perception. But it was only with the a...||3d kinect reconstruction indoor depth object recognition||link||2015-03-16||746|
|213||ChairGest Gestures||ChairGest is an open challenge / benchmark. The task consists in spotting and recognizing gestures from multiple synchronized sensors: 1 Kinect and 4 Xsens Ine...||benchmark recognition kinect gesture detection human||link||2014-06-06||755|
|183||MSR RGB-D 7-Scenes||The MSR RGB-D Dataset 7-Scenes dataset is a collection of tracked RGB-D camera frames. The dataset may be used for evaluation of methods for different applicati...||depth video kinect tracking location reconstruction||link||2013-09-05||971|
|171||CHALEARN Multi-modal Gesture Challenge||The CHALEARN Multi-modal Gesture Challenge is a dataset +700 sequences for gesture recognition using images, kinect depth, segmentation and skeleton data. ht...||gesture, kinect, recognition, human, action, illumination, depth, segmentation, skeleton||link||2013-08-09||909|
|170||Shefﬁeld Kinect Gesture (SKIG) dataset||The Shefﬁeld Kinect Gesture (SKIG) dataset contains 2160 hand gesture sequences (1080 RGB sequences and 1080 depth sequences) collected from 6 subjects. ...||gesture, kinect, recognition, human, action, illumination, depth||link||2017-12-02||1185|
|153||MSRC Kinect Gesture Dataset||The Microsoft Research Cambridge-12 Kinect gesture dataset consists of sequences of human movements, represented as body-part locations, and the associated gest...||gesture, kinect, recognition, human, action||link||2013-08-08||1039|
|149||NYU Depth v2||The 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 Microsoft Kinec...||semantic segmentation depth kinect label reconstruction||link||2017-06-01||2011|
|148||NYU Depth v1||The 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 Kinect. ...||semantic segmentation depth kinect label reconstruction||link||2014-10-05||1179|