19 papers
DST-Calib: A Dual-Path, Self-Supervised, Target-Free LiDAR-Camera Extrinsic Calibration Network
Zhiwei Huang, Yanwei Fu, Yi Zhou +3
LiDAR-camera extrinsic calibration is essential for multi-modal data fusion in robotic perception systems. However, existing approaches typically rely on handcrafted calibration ta…
Diffusion-Based Restoration for Multi-Modal 3D Object Detection in Adverse Weather
Zhijian He, Feifei Liu, Yuwei Li +4
Multi-modal 3D object detection is important for reliable perception in robotics and autonomous driving. However, its effectiveness remains limited under adverse weather conditions…
OMUDA: Omni-level Masking for Unsupervised Domain Adaptation in Semantic Segmentation
Yang Ou, Xiongwei Zhao, Xinye Yang +5
Unsupervised domain adaptation (UDA) enables semantic segmentation models to generalize from a labeled source domain to an unlabeled target domain. However, existing UDA methods st…
LiDAR-VGGT: Cross-Modal Coarse-to-Fine Fusion for Globally Consistent and Metric-Scale Dense Mapping
Lijie Wang, Lianjie Guo, Ziyi Xu +3
Reconstructing large-scale colored point clouds is an important task in robotics, supporting perception, navigation, and scene understanding. Despite advances in LiDAR inertial vis…
Grasp Like Humans: Learning Generalizable Multi-Fingered Grasping from Human Proprioceptive Sensorimotor Integration
Ce Guo, Xieyuanli Chen, Zhiwen Zeng +5
Tactile and kinesthetic perceptions are crucial for human dexterous manipulation, enabling reliable grasping of objects via proprioceptive sensorimotor integration. For robotic han…
A Pseudo Global Fusion Paradigm-Based Cross-View Network for LiDAR-Based Place Recognition
Jintao Cheng, Jiehao Luo, Xieyuanli Chen +4
LiDAR-based Place Recognition (LPR) remains a critical task in Embodied Artificial Intelligence (AI) and Autonomous Driving, primarily addressing localization challenges in GPS-den…