Tianchen Deng

ROADGS-T achieves superior road surface mapping by dynamically adjusting surfel density based on local geometric complexity, revolutionizing how we perceive road features in autonomous driving.

Forget rigid transforms: CAL2M's elastic sub-map alignment unlocks globally consistent kilometer-scale SLAM with Visual Geometry Foundation Models.

Achieve photorealistic multi-traversal 3D reconstruction by disentangling illumination from material properties, even when the same scene is captured under drastically different lighting conditions.

Robots can now use real-time environmental sounds to guide manipulation tasks, thanks to a new framework that overcomes the "Blind Execution Interval" of traditional vision-language-action models.