77 citations · 284 across the 23 of their papers we have counts for
6 papers · 1 filter
Learning Dense and Continuous Optical Flow from an Event Camera
Zhexiong Wan, Yuchao Dai, Yuxin Mao
Event cameras such as DAVIS can simultaneously output high temporal resolution events and low frame-rate intensity images, which own great potential in capturing scene motion, such…
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…
Deep Idempotent Network for Efficient Single Image Blind Deblurring
Yuxin Mao, Zhexiong Wan, Yuchao Dai +1
Single image blind deblurring is highly ill-posed as neither the latent sharp image nor the blur kernel is known. Even though considerable progress has been made, several major dif…
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…