17 citations · 49 across the 6 of their papers we have counts for
6 papers
Retro-FPN: Retrospective Feature Pyramid Network for Point Cloud Semantic Segmentation
Peng Xiang, Xin Wen, Yu-Shen Liu +3
Learning per-point semantic features from the hierarchical feature pyramid is essential for point cloud semantic segmentation. However, most previous methods suffered from ambiguou…
PMP-Net++: Point Cloud Completion by Transformer-Enhanced Multi-step Point Moving Paths
Xin Wen, Peng Xiang, Zhizhong Han +4
Point cloud completion concerns to predict missing part for incomplete 3D shapes. A common strategy is to generate complete shape according to incomplete input. However, unordered…
Snowflake Point Deconvolution for Point Cloud Completion and Generation with Skip-Transformer
Peng Xiang, Xin Wen, Yu-Shen Liu +4
Most existing point cloud completion methods suffer from the discrete nature of point clouds and the unstructured prediction of points in local regions, which makes it difficult to…
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results
Liang Pan, Tong Wu, Zhongang Cai +26
As real-scanned point clouds are mostly partial due to occlusions and viewpoints, reconstructing complete 3D shapes based on incomplete observations becomes a fundamental problem f…
SnowflakeNet: Point Cloud Completion by Snowflake Point Deconvolution with Skip-Transformer
Peng Xiang, Xin Wen, Yu-Shen Liu +4
Point cloud completion aims to predict a complete shape in high accuracy from its partial observation. However, previous methods usually suffered from discrete nature of point clou…
PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths
Xin Wen, Peng Xiang, Zhizhong Han +4
The task of point cloud completion aims to predict the missing part for an incomplete 3D shape. A widely used strategy is to generate a complete point cloud from the incomplete one…