2 code implementations • 9 Apr 2024 • Tianyu Huang, Haoang Li, Liangzu Peng, Yinlong Liu, Yun-hui Liu
Our strategy largely reduces the search space and can guarantee accuracy with only a few inlier samples, therefore enjoying an excellent trade-off between efficiency and robustness.
no code implementations • 2 Nov 2023 • Xinyi Li, Zijian Ma, Yinlong Liu, Walter Zimmer, Hu Cao, Feihu Zhang, Alois Knoll
This paper focuses on addressing the robust correspondence-based registration problem with gravity prior that often arises in practice.
no code implementations • 19 May 2023 • Xinyi Li, Yinlong Liu, Hu Cao, Xueli Liu, Feihu Zhang, Alois Knoll
Estimating the rigid transformation between two LiDAR scans through putative 3D correspondences is a typical point cloud registration paradigm.
1 code implementation • ICCV 2021 • Fan Lu, Guang Chen, Yinlong Liu, Lijun Zhang, Sanqing Qu, Shu Liu, Rongqi Gu
Extensive experiments are conducted on two large-scale outdoor LiDAR point cloud datasets to demonstrate the high accuracy and efficiency of the proposed HRegNet.
1 code implementation • 18 Dec 2020 • Fan Lu, Guang Chen, Sanqing Qu, Zhijun Li, Yinlong Liu, Alois Knoll
Generally, the frame rates of mechanical LiDAR sensors are 10 to 20 Hz, which is much lower than other commonly used sensors like cameras.
no code implementations • 21 Nov 2020 • Fan Lu, Guang Chen, Yinlong Liu, Zhijun Li, Sanqing Qu, Tianpei Zou
3D point clouds accurately model 3D information of surrounding environment and are crucial for intelligent vehicles to perceive the scene.
1 code implementation • NeurIPS 2020 • Fan Lu, Guang Chen, Yinlong Liu, Zhongnan Qu, Alois Knoll
To tackle the information loss of random sampling, we exploit a novel random dilation cluster strategy to enlarge the receptive field of each sampled point and an attention mechanism to aggregate the positions and features of neighbor points.
1 code implementation • 29 Apr 2019 • Yinlong Liu, Alois Knoll, Guang Chen
Accordingly, we propose a vertical direction estimation method by considering the relationship between the vertical frame and horizontal frames.
no code implementations • 25 Mar 2019 • Yinlong Liu, Xuechen Li, Manning Wang, Guang Chen, Zhijian Song, Alois Knoll
In this paper, we consider pairwise constraints and propose a globally optimal algorithm for solving the absolute pose estimation problem.
no code implementations • 29 Dec 2018 • Xuechen Li, Yinlong Liu, Yiru Wang, Chen Wang, Manning Wang, Zhijian Song
However, the existing global methods are slow for two main reasons: the computational complexity of BnB is exponential to the problem dimensionality (which is six for 3D rigid registration), and the bound evaluation used in BnB is inefficient.
no code implementations • ECCV 2018 • Yinlong Liu, Chen Wang, Zhijian Song, Manning Wang
Three-dimensional rigid point cloud registration has many applications in computer vision and robotics.