View-Guided Point Cloud Completion
Xuancheng Zhang, Yutong Feng, Siqi Li, Changqing Zou, Hai Wan, Xibin Zhao, Yandong Guo, Yue Gao
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.
Results
| Task | Dataset | Metric | Value | Model |
|---|---|---|---|---|
| Point Cloud Generation | ShapeNet-ViPC | Chamfer Distance | 3.308 | ViPC |
| Point Cloud Completion | ShapeNet-ViPC | Chamfer Distance | 3.308 | ViPC |
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