3 papers
cs.CV2025
Customizing Visual-Language Foundation Models for Multi-modal Anomaly Detection and Reasoning
Xiaohao Xu, Yunkang Cao, Huaxin Zhang +2
Anomaly detection is vital in various industrial scenarios, including the identification of unusual patterns in production lines and the detection of manufacturing defects for qual…
cs.CV2024
Is Your LiDAR Placement Optimized for 3D Scene Understanding?
Ye Li, Lingdong Kong, Hanjiang Hu +2
The reliability of driving perception systems under unprecedented conditions is crucial for practical usage. Latest advancements have prompted increasing interest in multi-LiDAR pe…
cs.CV2024
Learning Shared RGB-D Fields: Unified Self-supervised Pre-training for Label-efficient LiDAR-Camera 3D Perception
Xiaohao Xu, Ye Li, Tianyi Zhang +3
Constructing large-scale labeled datasets for multi-modal perception model training in autonomous driving presents significant challenges. This has motivated the development of sel…