Qi Li 1, Tzu-Chen Chiu 2, Hsiang-Wei Huang 2, Min-Te Sun2, Wei-Shinn Ku 1
1 Auburn University Auburn, United States, 2 National Central University Taoyuan City, Taiwan
Our dataset is available at VideoBadminton.
Methods | Backbone | Top1 Acc | Top5 Acc | Mean Cls Acc | Models trained on VideoBadminton |
---|---|---|---|---|---|
R(2+1)D | ResNet2Plus1d | 79.53% | 96.11% | 66.97% | R(2+1)D |
SlowFast | ResNet3dSlowFast | 82.80% | 97.54% | 73.80% | SlowFast |
TimeSformer | TimeSformer | 73.18% | 94.78% | 57.70% | TimeSformer |
Swim | SwinTransformer3D | 81.99% | 96.52% | 69.93% | Swim |
MViT-V2 | MViT | 14.23% | 62.23% | 10.76% | MViT-V2 |
ST-GCN | RecognizerGCN | 74.41% | 93.76% | 61.44% | ST-GCN |
PoseC3D | Recognizer3D | 80.76% | 96.01% | 67.18% | PoseC3D |
- The train and validation sets are split as follows: