V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditions

arXiv:2403.11371v1 Announce Type: new
Abstract: Current LiDAR-based Vehicle-to-Everything (V2X) multi-agent perception systems have shown the significant success on 3D object detection. While these models perform well in the trained clean weather, they struggle in unseen adverse weather conditions with the real-world domain gap. In this paper, we propose a domain generalization approach, named V2X-DGW, for LiDAR-based 3D object detection on multi-agent perception system under adverse weather conditions. Not only in the clean weather does our research aim to ensure favorable …

3d object 3d object detection abstract agent arxiv cs.cv current detection domain everything gap lidar multi-agent object paper perception struggle success systems type weather world