5 papers
CLLAP: Contrastive Learning-based LiDAR-Augmented Pretraining for Enhanced Radar-Camera Fusion
Bingyi Liu, Chuanhui Zhu, Hongfei Xue +5
Accurate 3D object detection is critical for autonomous driving, necessitating reliable, cost-effective sensors capable of operating in adverse weather conditions. Camera and milli…
Send Less, Perceive More: Masked Quantized Point Cloud Communication for Loss-Tolerant Collaborative Perception
Sheng Xu, Enshu Wang, Hongfei Xue +6
Collaborative perception allows connected vehicles to overcome occlusions and limited viewpoints by sharing sensory information. However, existing approaches struggle to achieve hi…
InfoCom: Kilobyte-Scale Communication-Efficient Collaborative Perception with Information Bottleneck
Quanmin Wei, Penglin Dai, Wei Li +2
Precise environmental perception is critical for the reliability of autonomous driving systems. While collaborative perception mitigates the limitations of single-agent perception…
Pragmatic Heterogeneous Collaborative Perception via Generative Communication Mechanism
Junfei Zhou, Penglin Dai, Quanmin Wei +3
Multi-agent collaboration enhances the perception capabilities of individual agents through information sharing. However, in real-world applications, differences in sensors and mod…
CoPEFT: Fast Adaptation Framework for Multi-Agent Collaborative Perception with Parameter-Efficient Fine-Tuning
Quanmin Wei, Penglin Dai, Wei Li +2
Multi-agent collaborative perception is expected to significantly improve perception performance by overcoming the limitations of single-agent perception through exchanging complem…