Trajectory Convolution for Action Recognition

ADVANCES IN NEURAL INFORMATION PROCESSING SYSTEMS 31 (NIPS 2018), pp. 2208-2219, 2018.

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practical applicationsfeature learningaction recognitiontemporal dimensionvideo analysisMore(2+)

Abstract:

How to leverage the temporal dimension is one major question in video analysis. Recent works [47, 36] suggest an efficient approach to video feature learning, i.e., factorizing 3D convolutions into separate components respectively for spatial and temporal convolutions. The temporal convolution, however, comes with an implicit assumption -...More

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