  We introduce a new public video dataset for action recognition: Anonymized
Videos from Diverse countries (AViD). Unlike existing public video datasets,
AViD is a collection of action videos from many different countries. The
motivation is to create a public dataset that would benefit training and
pretraining of action recognition models for everybody, rather than making it
useful for limited countries. Further, all the face identities in the AViD
videos are properly anonymized to protect their privacy. It also is a static
dataset where each video is licensed with the creative commons license. We
confirm that most of the existing video datasets are statistically biased to
only capture action videos from a limited number of countries. We
experimentally illustrate that models trained with such biased datasets do not
transfer perfectly to action videos from the other countries, and show that
AViD addresses such problem. We also confirm that the new AViD dataset could
serve as a good dataset for pretraining the models, performing comparably or
better than prior datasets.
