TSM: Temporal Shift Module for Efficient Video Understanding
© 2019 IEEE. The explosive growth in video streaming gives rise to challenges on performing video understanding at high accuracy and low computation cost. Conventional 2D CNNs are computationally cheap but cannot capture temporal relationships; 3D CNN based methods can achieve good performance but a...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2022
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| Online Access: | https://hdl.handle.net/1721.1/143615 |