Robust 3D perception for autonomous driving
Cooperative and all-weather multimodal perception for reliable autonomous systems.
This research develops 3D perception systems that learn from cooperative observations and remain robust across weather and sensor domains.
Representative work includes unsupervised multi-agent supervision for single-agent perception and DA3D, a domain-aware adaptation method for all-weather LiDAR-radar 3D detection.