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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 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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