2 citations · 5 across the 5 of their papers we have counts for
6 papers
CoST: Efficient Collaborative Perception From Unified Spatiotemporal Perspective
Zongheng Tang, Yi Liu, Yifan Sun +4
Collaborative perception shares information among different agents and helps solving problems that individual agents may face, e.g., occlusions and small sensing range. Prior metho…
CoCMT: Communication-Efficient Cross-Modal Transformer for Collaborative Perception
Rujia Wang, Xiangbo Gao, Hao Xiang +2
Multi-agent collaborative perception enhances each agent perceptual capabilities by sharing sensing information to cooperatively perform robot perception tasks. This approach has p…
STAMP: Scalable Task And Model-agnostic Collaborative Perception
Xiangbo Gao, Runsheng Xu, Jiachen Li +3
Perception is crucial for autonomous driving, but single-agent perception is often constrained by sensors' physical limitations, leading to degraded performance under severe occlus…
CoMamba: Real-time Cooperative Perception Unlocked with State Space Models
Jinlong Li, Xinyu Liu, Baolu Li +4
Cooperative perception systems play a vital role in enhancing the safety and efficiency of vehicular autonomy. Although recent studies have highlighted the efficacy of vehicle-to-e…
Light the Night: A Multi-Condition Diffusion Framework for Unpaired Low-Light Enhancement in Autonomous Driving
Jinlong Li, Baolu Li, Zhengzhong Tu +5
Vision-centric perception systems for autonomous driving have gained considerable attention recently due to their cost-effectiveness and scalability, especially compared to LiDAR-b…
V2X-DGW: Domain Generalization for Multi-agent Perception under Adverse Weather Conditions
Baolu Li, Jinlong Li, Xinyu Liu +5
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 tra…