8 papers · 1 filter
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…
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…
Domain Adaptation based Object Detection for Autonomous Driving in Foggy and Rainy Weather
Jinlong Li, Runsheng Xu, Xinyu Liu +5
Typically, object detection methods for autonomous driving that rely on supervised learning make the assumption of a consistent feature distribution between the training and testin…
VehicleGAN: Pair-flexible Pose Guided Image Synthesis for Vehicle Re-identification
Baolu Li, Ping Liu, Lan Fu +4
Vehicle Re-identification (Re-ID) has been broadly studied in the last decade; however, the different camera view angle leading to confused discrimination in the feature subspace f…
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…
Breaking Data Silos: Cross-Domain Learning for Multi-Agent Perception from Independent Private Sources
Jinlong Li, Baolu Li, Xinyu Liu +3
The diverse agents in multi-agent perception systems may be from different companies. Each company might use the identical classic neural network architecture based encoder for fea…