SAST: Learning Semantic Action-Aware Spatial-Temporal Features for Efficient Action Recognition
The state-of-the-arts in action recognition are suffering from three challenges: (1) How to model spatial transformations of action since it is always geometric variation over time in videos. (2) How to develop the semantic action-aware temporal features from one video with a large proportion of irr...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8896926/ |