6 papers
DCReg: Decoupled Characterization for Efficient Degenerate LiDAR Registration
Xiangcheng Hu, Xieyuanli Chen, Mingkai Jia +3
LiDAR point cloud registration is fundamental to robotic perception and navigation. In geometrically degenerate environments (e.g., corridors), registration becomes ill-conditioned…
Efficient Point Cloud Processing with High-Dimensional Positional Encoding and Non-Local MLPs
Yanmei Zou, Hongshan Yu, Yaonan Wang +4
Multi-Layer Perceptron (MLP) models are the foundation of contemporary point cloud processing. However, their complex network architectures obscure the source of their strength and…
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…