67 citations · 110 across the 5 of their papers we have counts for
5 papers
Learning a Task-specific Descriptor for Robust Matching of 3D Point Clouds
Zhiyuan Zhang, Yuchao Dai, Bin Fan +2
Existing learning-based point feature descriptors are usually task-agnostic, which pursue describing the individual 3D point clouds as accurate as possible. However, the matching t…
CU-Net: LiDAR Depth-Only Completion With Coupled U-Net
Yufei Wang, Yuchao Dai, Qi Liu +3
LiDAR depth-only completion is a challenging task to estimate dense depth maps only from sparse measurement points obtained by LiDAR. Even though the depth-only methods have been w…
Searching Dense Point Correspondences via Permutation Matrix Learning
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +2
Although 3D point cloud data has received widespread attentions as a general form of 3D signal expression, applying point clouds to the task of dense correspondence estimation betw…
VRNet: Learning the Rectified Virtual Corresponding Points for 3D Point Cloud Registration
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +2
3D point cloud registration is fragile to outliers, which are labeled as the points without corresponding points. To handle this problem, a widely adopted strategy is to estimate t…
A Representation Separation Perspective to Correspondences-free Unsupervised 3D Point Cloud Registration
Zhiyuan Zhang, Jiadai Sun, Yuchao Dai +3
3D point cloud registration in remote sensing field has been greatly advanced by deep learning based methods, where the rigid transformation is either directly regressed from the t…