187 citations · 402 across the 16 of their papers we have counts for
7 papers · 1 filter
CSformer: Bridging Convolution and Transformer for Compressive Sensing
Dongjie Ye, Zhangkai Ni, Hanli Wang +3
Convolution neural networks (CNNs) have succeeded in compressive image sensing. However, due to the inductive bias of locality and weight sharing, the convolution operations demons…
COTReg:Coupled Optimal Transport based Point Cloud Registration
Guofeng Mei, Xiaoshui Huang, Litao Yu +2
Generating a set of high-quality correspondences or matches is one of the most critical steps in point cloud registration. This paper proposes a learning framework COTReg by jointl…
GenReg: Deep Generative Method for Fast Point Cloud Registration
Xiaoshui Huang, Zongyi Xu, Guofeng Mei +4
Accurate and efficient point cloud registration is a challenge because the noise and a large number of points impact the correspondence search. This challenge is still a remaining…
Dyn-Backdoor: Backdoor Attack on Dynamic Link Prediction
Jinyin Chen, Haiyang Xiong, Haibin Zheng +3
Dynamic link prediction (DLP) makes graph prediction based on historical information. Since most DLP methods are highly dependent on the training data to achieve satisfying predict…
Learning Disentangled Representation Implicitly via Transformer for Occluded Person Re-Identification
Mengxi Jia, Xinhua Cheng, Shijian Lu +1
Person re-identification (re-ID) under various occlusions has been a long-standing challenge as person images with different types of occlusions often suffer from misalignment in i…
Super-Resolving Compressed Video in Coding Chain
Dewang Hou, Yang Zhao, Yuyao Ye +3
Scaling and lossy coding are widely used in video transmission and storage. Previous methods for enhancing the resolution of such videos often ignore the inherent interference betw…
A comprehensive survey on point cloud registration
Xiaoshui Huang, Guofeng Mei, Jian Zhang +1
Registration is a transformation estimation problem between two point clouds, which has a unique and critical role in numerous computer vision applications. The developments of opt…