22 citations · 47 across the 7 of their papers we have counts for
7 papers
Explicitly Guided Information Interaction Network for Cross-modal Point Cloud Completion
Hang Xu, Chen Long, Wenxiao Zhang +4
In this paper, we explore a novel framework, EGIInet (Explicitly Guided Information Interaction Network), a model for View-guided Point cloud Completion (ViPC) task, which aims to…
SparseDC: Depth Completion from sparse and non-uniform inputs
Chen Long, Wenxiao Zhang, Zhe Chen +5
We propose SparseDC, a model for Depth Completion of Sparse and non-uniform depth inputs. Unlike previous methods focusing on completing fixed distributions on benchmark datasets (…
DGECN: A Depth-Guided Edge Convolutional Network for End-to-End 6D Pose Estimation
Tuo Cao, Fei Luo, Yanping Fu +3
Monocular 6D pose estimation is a fundamental task in computer vision. Existing works often adopt a two-stage pipeline by establishing correspondences and utilizing a RANSAC algori…
KTNet: Knowledge Transfer for Unpaired 3D Shape Completion
Zhen Cao, Wenxiao Zhang, Xin Wen +4
Unpaired 3D object completion aims to predict a complete 3D shape from an incomplete input without knowing the correspondence between the complete and incomplete shapes. In this pa…
PC-PU: Patch Correlation and Point Correlation for Effective Point Cloud Upsampling
Chen Long, Wenxiao Zhang, Ruihui Li +3
Point cloud upsampling is to densify a sparse point set acquired from 3D sensors, providing a denser representation for the underlying surface. Existing methods divide the input po…
Detail Preserved Point Cloud Completion via Separated Feature Aggregation
Wenxiao Zhang, Qingan Yan, Chunxia Xiao
Point cloud shape completion is a challenging problem in 3D vision and robotics. Existing learning-based frameworks leverage encoder-decoder architectures to recover the complete s…
PCAN: 3D Attention Map Learning Using Contextual Information for Point Cloud Based Retrieval
Wenxiao Zhang, Chunxia Xiao
Point cloud based retrieval for place recognition is an emerging problem in vision field. The main challenge is how to find an efficient way to encode the local features into a dis…