3 papers
cs.CV2026
LEADER: Learning Reliable Local-to-Global Correspondences for LiDAR Relocalization
Jianshi Wu, Minghang Zhu, Dunqiang Liu +5
LiDAR relocalization has attracted increasing attention as it can deliver accurate 6-DoF pose estimation in complex 3D environments. Recent learning-based regression methods offer…
cs.CV2026
From Single Scan to Sequential Consistency: A New Paradigm for LIDAR Relocalization
Minghang Zhu, Zhijing Wang, Yuxin Guo +3
LiDAR relocalization aims to estimate the global 6-DoF pose of a sensor in the environment. However, existing regression-based approaches are prone to dynamic or ambiguous scenario…
cs.CV2025
MoniRefer: A Real-world Large-scale Multi-modal Dataset based on Roadside Infrastructure for 3D Visual Grounding
Panquan Yang, Junfei Huang, Zongzhangbao Yin +9
3D visual grounding aims to localize the object in 3D point cloud scenes that semantically corresponds to given natural language sentences. It is very critical for roadside infrast…