1 code implementation • 23 May 2023 • Xuecheng Xu, Yanmei Jiao, Sha Lu, Xiaqing Ding, Rong Xiong, Yue Wang
In addition, the image and point cloud cues can be easily stated in the same coordinates, which benefits sensor fusion for place recognition.
no code implementations • 2 Mar 2022 • Xiaqing Ding, Xuecheng Xu, Sha Lu, Yanmei Jiao, Mengwen Tan, Rong Xiong, Huanjun Deng, Mingyang Li, Yue Wang
Global point cloud registration is an essential module for localization, of which the main difficulty exists in estimating the rotation globally without initial value.
1 code implementation • 14 Dec 2020 • Yiyuan Pan, Xuecheng Xu, Xiaqing Ding, Shoudong Huang, Yue Wang, Rong Xiong
As a result, this deformable global dense map representation is able to keep the global consistency online.
no code implementations • 24 Oct 2020 • Xiaqing Ding, Yue Wang, Li Tang, Yanmei Jiao, Rong Xiong
Through experiments on real world RGBD datasets we validate the effectiveness of our design in terms of improving both generalization performance and robustness towards viewpoint change, and also show the potential of regression based visual localization networks towards challenging occasions that are difficult for geometry based visual localization methods.
1 code implementation • 6 Dec 2017 • Huan Yin, Li Tang, Xiaqing Ding, Yue Wang, Rong Xiong
Global localization in 3D point clouds is a challenging problem of estimating the pose of vehicles without any prior knowledge.