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Found 1 papers, 1 papers with code
Learning Temporally Invariant and Localizable Features via Data Augmentation for Video Recognition
Based on our novel temporal data augmentation algorithms, video recognition performances are improved using only a limited amount of training data compared to the spatial-only data augmentation algorithms, including the 1st Visual Inductive Priors (VIPriors) for data-efficient action recognition challenge.
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