Papers › GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer
GaitMixer: Skeleton-based Gait Representation Learning via Wide-spectrum Multi-axial Mixer
Ekkasit Pinyoanuntapong, Ayman Ali, Pu Wang, Minwoo Lee, Chen Chen
Most existing gait recognition methods are appearance-based, which rely on the silhouettes extracted from the video data of human walking activities. The less-investigated skeleton-based gait recognition methods directly learn the gait dynamics from 2D/3D human skeleton sequences, which are theoretically more robust solutions in the presence of appearance changes caused by clothes, hairstyles, and carrying objects. However, the performance of skeleton-based solutions is still largely behind the appearance-based ones. This paper aims to close such performance gap by proposing a novel network model, GaitMixer, to learn more discriminative gait representation from skeleton sequence data. In particular, GaitMixer follows a heterogeneous multi-axial mixer architecture, which exploits the spatial self-attention mixer followed by the temporal large-kernel convolution mixer to learn rich multi-frequency signals in the gait feature maps. Experiments on the widely used gait database, CASIA-B, demonstrate that GaitMixer outperforms the previous SOTA skeleton-based methods by a large margin while achieving a competitive performance compared with the representative appearance-based solutions. Code will be available at https://github.com/exitudio/gaitmixer
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Code
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Tasks
Results from the paper archive 2025-07-28
| Task | Dataset | Model | Metric | Value | Rank at snapshot | Leaderboard | Report |
|---|---|---|---|---|---|---|---|
| Multiview Gait Recognition | CASIA-B | GaitMixer | Accuracy (Cross-View, Avg) | 88.3 | #9 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitMixer | BG#1-2 | 85.6 | #9 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitMixer | CL#1-2 | 84.5 | #9 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitMixer | NM#5-6 | 94.9 | #9 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitFormer | Accuracy (Cross-View, Avg) | 83.4 | #11 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitFormer | BG#1-2 | 81.4 | #11 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitFormer | CL#1-2 | 77.2 | #11 of 12 | Archive leaderboard | report |
| Multiview Gait Recognition | CASIA-B | GaitFormer | NM#5-6 | 91.5 | #11 of 12 | Archive leaderboard | report |
Ranks are positions in the archive's leaderboards as they stood at the 2025-07-28 snapshot. Results published since then are not among these rows, so a rank here is not a current standing.
Methods
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