This paper proposes the first cross-modality gait recognition framework, named CrossGait, that bridges the gap between LiDAR point clouds and camera silhouettes for accurate pedestrian identification across diverse sensors.
Gait recognition can be improved by fusing silhouette and skeleton representations, and refining the skeleton data using temporal consistency from silhouettes.