English

View-Guided Point Cloud Completion

Computer Vision and Pattern Recognition 2021-04-14 v2

Abstract

This paper presents a view-guided solution for the task of point cloud completion. Unlike most existing methods directly inferring the missing points using shape priors, we address this task by introducing ViPC (view-guided point cloud completion) that takes the missing crucial global structure information from an extra single-view image. By leveraging a framework that sequentially performs effective cross-modality and cross-level fusions, our method achieves significantly superior results over typical existing solutions on a new large-scale dataset we collect for the view-guided point cloud completion task.

Keywords

Cite

@article{arxiv.2104.05666,
  title  = {View-Guided Point Cloud Completion},
  author = {Xuancheng Zhang and Yutong Feng and Siqi Li and Changqing Zou and Hai Wan and Xibin Zhao and Yandong Guo and Yue Gao},
  journal= {arXiv preprint arXiv:2104.05666},
  year   = {2021}
}

Comments

10 pages, 8 figures, CVPR2021