Gongxin Yao — accepted AI-conference papers

2025

Monocular Visual Place Recognition in LiDAR Maps via Cross-Modal State Space Model and Multi-View Matching

Gongxin Yao, Xinyang Li, Luowei Fu, Yu Pan

ICRA 2025

Achieving monocular camera localization within pre-built LiDAR maps can bypass the simultaneous mapping process of visual SLAM systems, potentially reducing the computational overhead of autonomous localization. To this end, one of the key challenges is cross-modal place recognition, which involves

Cited by 3 Source ↗code ↗Scholar ↗

2024

CMR-Agent: Learning a Cross-Modal Agent for Iterative Image-to-Point Cloud Registration

Gongxin Yao, Yixin Xuan, Xinyang Li, Yu Pan

IROS 2024

Image-to-point cloud registration aims to determine the relative camera pose of an RGB image with respect to a point cloud. It plays an important role in camera localization within pre-built LiDAR maps. Despite the modality gaps, most learning-based methods establish 2D-3D point correspondences in f

Cited by 2 Source ↗Scholar ↗