Abstract:In the field of action recognition based on RGB videos, it is infeasible to train deep networks on dozens or hundreds of frames because of limits on computational complexity and memory. Previous works commonly adopted a sparse sampling strategy, which unfortunately leads to missing crucial frames and insufficient modelling for short‐range motions. In this letter, an effective motion information aggregation module (MIAM) that utilises convolutional neural networks to aggregate motion information from multiple f… Show more
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