Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
6938619 | Pattern Recognition | 2019 | 39 Pages |
Abstract
The asymmetric 3D-CNN model is evaluated on two of the most challenging action recognition benchmarks, UCF-101 and HMDB-51. The asymmetric 3D-CNN model outperforms all the traditional 3D-CNN models in both effectiveness and efficiency, and its performance is comparable with that of recent state-of-the-art action recognition methods on both benchmarks.
Keywords
Related Topics
Physical Sciences and Engineering
Computer Science
Computer Vision and Pattern Recognition
Authors
Hao Yang, Chunfeng Yuan, Bing Li, Yang Du, Junliang Xing, Weiming Hu, Stephen J. Maybank,