63 citations · 74 across the 7 of their papers we have counts for
7 papers
Deep Recurrent Neural Network with Multi-scale Bi-directional Propagation for Video Deblurring
Chao Zhu, Hang Dong, Jinshan Pan +4
The success of the state-of-the-art video deblurring methods stems mainly from implicit or explicit estimation of alignment among the adjacent frames for latent video restoration.…
3D Registration for Self-Occluded Objects in Context
Zheng Dang, Fei Wang, Mathieu Salzmann
While much progress has been made on the task of 3D point cloud registration, there still exists no learning-based method able to estimate the 6D pose of an object observed by a 2.…
A Method to Generate High Precision Mesh Model and RGB-D Datasetfor 6D Pose Estimation Task
Minglei Lu, Yu Guo, Fei Wang +1
Recently, 3D version has been improved greatly due to the development of deep neural networks. A high quality dataset is important to the deep learning method. Existing datasets fo…
Learning 3D-3D Correspondences for One-shot Partial-to-partial Registration
Zheng Dang, Fei Wang, Mathieu Salzmann
While 3D-3D registration is traditionally tacked by optimization-based methods, recent work has shown that learning-based techniques could achieve faster and more robust results. I…
Multi-Scale Boosted Dehazing Network with Dense Feature Fusion
Hang Dong, Jinshan Pan, Lei Xiang +4
In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature Fusion based on the U-Net architecture. The proposed method is designed based on two principles,…
Eigendecomposition-Free Training of Deep Networks for Linear Least-Square Problems
Zheng Dang, Kwang Moo Yi, Yinlin Hu +3
Many classical Computer Vision problems, such as essential matrix computation and pose estimation from 3D to 2D correspondences, can be tackled by solving a linear least-square pro…