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View-Guided Point Cloud Completion

About

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.

Xuancheng Zhang, Yutong Feng, Siqi Li, Changqing Zou, Hai Wan, Xibin Zhao, Yandong Guo, Yue Gao• 2021

Related benchmarks

TaskDatasetResultRank
Point Cloud CompletionPCN (test)
Average (L1 CD)8.06
67
Point Cloud CompletionShapeNet-ViPC supervised (test)
Mean F-Score @ 0.001 (Avg)59.1
16
Point Cloud CompletionShapeNet-ViPC (known categories)
Avg Score0.591
13
Point Cloud CompletionShapeNet-ViPC (test)
MCD (Airplane)1.76
10
Point Cloud CompletionShapeNet-ViPC Novel categories
MCD (Avg)4.601
8
Point Cloud CompletionShapeNet-ViPC Novel categories (test)
F-Score@0.001 (Avg)49.8
8
Point Cloud CompletionShapNet-ViPC
mIoU (Avg)59.1
5
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