Faster and Accurate Compressed Video Action Recognition Straight from the Frequency Domain
Author:
Funder
Microsoft Research
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9265968/9265969/09265987.pdf?arnumber=9265987
Cited by 17 articles. 订阅此论文施引文献 订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献
1. F2D-SIFPNet: a frequency 2D Slow-I-Fast-P network for faster compressed video action recognition;Applied Intelligence;2024-04
2. Action recognition in compressed domains: A survey;Neurocomputing;2024-04
3. A video compression-cum-classification network for classification from compressed video streams;The Visual Computer;2024-03-08
4. Frequency Enhancement Network for Efficient Compressed Video Action Recognition;2023 IEEE International Conference on Image Processing (ICIP);2023-10-08
5. FSConformer: A Frequency-Spatial-Domain CNN-Transformer Two-Stream Network for Compressed Video Action Recognition;2023 IEEE Smart World Congress (SWC);2023-08-28
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