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网址:Yet Another Computer Vision Index To Datasets (YACVID)
网址:Deep Learning Datasets | DeepLearning.buzz
This is a collated list of image and video databases that people have found useful for computer vision research and algorithm evaluation.
An important article:
How Good Is My Test Data? Introducing Safety Analysis for Computer Vision
(by Zendel, Murschitz, Humenberger, and Herzner)
introduces a methodology for ensuring that your dataset has sufficient
variety that algorithm results on the dataset are representative of
the results that one could expect in a real setting.
In particular, the team have produced a
Checklist of potential
hazards (imaging situations) that may cause algorithms to have problems.
Ideally, test datasets should have examples of the relevant hazards.
Another helpful site is the YACVID page.
See also:
Action Recognition’s dataset summary with league tables (Gall, Kuehne, Bhattarai).
Note: there are 3D datasets elsewhere as well, e.g. in
Objects, Scenes, and Actions.
Acknowledgements: Many thanks to all of the contributors for their suggestions of databases.
Can PU was very helpful with the updating of this web page.
Source – http://homepages.inf.ed.ac.uk/rbf/CVonline/Imagedbase.htm
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