Papers › Make Skeleton-based Action Recognition Model Smaller, Faster and Better
Make Skeleton-based Action Recognition Model Smaller, Faster and Better
Fan Yang, Sakriani Sakti, Yang Wu, Satoshi Nakamura
Although skeleton-based action recognition has achieved great success in recent years, most of the existing methods may suffer from a large model size and slow execution speed. To alleviate this issue, we analyze skeleton sequence properties to propose a Double-feature Double-motion Network (DD-Net) for skeleton-based action recognition. By using a lightweight network structure (i.e., 0.15 million parameters), DD-Net can reach a super fast speed, as 3,500 FPS on one GPU, or, 2,000 FPS on one CPU. By employing robust features, DD-Net achieves the state-of-the-art performance on our experimental datasets: SHREC (i.e., hand actions) and JHMDB (i.e., body actions). Our code will be released with this paper later.
Code
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Tasks
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Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Hand Gesture Recognition | DHG-14 | DD-Net | Accuracy | 94.6 | #3 of 13 | Archive leaderboard | report |
| Hand Gesture Recognition | DHG-28 | DD-Net | Accuracy | 91.9 | #3 of 9 | Archive leaderboard | report |
| Hand Gesture Recognition | SHREC 2017 track on 3D Hand Gesture Recognition | DD-Net | 14 gestures accuracy | 94.6 | #3 of 3 | Archive leaderboard | report |
| Skeleton Based Action Recognition | J-HMDB | DD-Net | Accuracy (RGB+pose) | - | #12 of 13 | Archive leaderboard | report |
| Skeleton Based Action Recognition | J-HMDB | DD-Net | Accuracy (pose) | 77.2 | #12 of 13 | Archive leaderboard | report |
| Skeleton Based Action Recognition | JHMDB (2D poses only) | DD-Net | Accuracy | 78.0 (average of 3 split train/test) | #2 of 6 | Archive leaderboard | report |
| Skeleton Based Action Recognition | JHMDB (2D poses only) | DD-Net | Average accuracy of 3 splits | 77.2 | #2 of 6 | Archive leaderboard | report |
| Skeleton Based Action Recognition | JHMDB (2D poses only) | DD-Net | No. parameters | 1.82 M | #2 of 6 | Archive leaderboard | report |
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