AQA-7 - Dataset for assessing the quality of 7 different actions.An analyzed collation of various labeled video datasets for action recognition (Kevin Murphy).Actor and Action Dataset - 3782 videos, seven classes of actors performing eight different actions (Xu, Hsieh, Xiong, Corso).Action Detection in Videos - MERL Shopping Dataset consists of 106 videos, each of which is a sequence about 2 minutes long (Michael Jones, Tim Marks).

ActivityNet - A Large-Scale Video Benchmark for Human Activity Understanding (200 classes, 100 videos per class, 648 video hours) (Heilbron, Escorcia, Ghanem and Niebles).

A first-person vision dataset of office activities (FPVO) - FPVO contains first-person video segments of office activities collected using 12 participants.

50 Salads - fully annotated 4.5 hour dataset of RGB-D video + accelerometer data, capturing 25 people preparing two mixed salads each (Dundee University, Sebastian Stein).

3D online action dataset - There are seven action categories (Microsoft and Nanyang Technological University).

Something-something v2 - 220847 video clips involving actions between 2 objects (30408 objects, 174 labels) (Goyal, Kahou, Michalski, Materzynska, Westphal, Kim, Haenel, Fruend, Yianilos, Mueller-Freitag, Hoppe, Thurau, Bax, Memisevic).

108499 video clips involving actions between 2 objects, 174 labels)(Twenty Billion Neurons GmbH)

20bn-Something-Something - densely-labeled video clips that show humans performing predefined basic actions with everyday objects.

19NonSense - a non-obstructive sensing based and fully annotated accelerometer and gyroscope data of 19 activities under multiple contexts, capturing 13 subjects wearing e-Shoes and a smart watch (Thi-Lan Le).YACVID - a tagged index to some computer vision datasetsĪction Recognition's dataset summary with league tables (Gall, Kuehne, Bhattarai).Academic Torrents - computer vision - a set of 30+ large datasets available in BitTorrent form.Surveillance and Tracking (See also People).Scenes or Places, Scene Segmentation or Classification.People Detection and Tracking Databases (See also Surveillance).People (static and dynamic), human body pose.Image, Video and Shape Database Retrieval.Hand, Hand Grasp, Hand Action and Gesture Databases.General RGBD, 3D Point Cloud, and depth datasets.Ideally, test datasets should have examples of the relevant hazards. Hazards (imaging situations) that may cause algorithms to have problems. The results that one could expect in a real setting. Variety that algorithm results on the dataset are representative of

Introduces a methodology for ensuring that your dataset has sufficient (by Zendel, Murschitz, Humenberger, and Herzner) How Good Is My Test Data? Introducing Safety Analysis for Computer Vision Have found useful for computer vision research and algorithm evaluation. This is a collated list of image and video databases that people

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