Point Cloud Completion
76 papers with code • 3 benchmarks • 5 datasets
Benchmarks
These leaderboards are used to track progress in Point Cloud Completion
| Trend | Dataset | Best Model | Paper | Code | Compare |
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ShapeNet
Completion3D
MVP
ShapeNet-ViPC
VBR
Most implemented papers
PMP-Net: Point Cloud Completion by Learning Multi-step Point Moving Paths
diviswen/PMP-Net
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CVPR 2021
As a result, the network learns a strict and unique correspondence on point-level, which can capture the detailed topology and structure relationships between the incomplete shape and the complete target, and thus improves the quality of the predicted complete shape.
HyperPocket: Generative Point Cloud Completion
gmum/3d-point-clouds-autocomplete
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In this work, we reformulate the problem of point cloud completion into an object hallucination task.
Style-based Point Generator with Adversarial Rendering for Point Cloud Completion
microsoft/SpareNet
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CVPR 2021
In this paper, we proposed a novel Style-based Point Generator with Adversarial Rendering (SpareNet) for point cloud completion.
Cycle4Completion: Unpaired Point Cloud Completion using Cycle Transformation with Missing Region Coding
diviswen/Cycle4Completion
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CVPR 2021
We provide a comprehensive evaluation in experiments, which shows that our model with the learned bidirectional geometry correspondence outperforms state-of-the-art unpaired completion methods.
Denoise and Contrast for Category Agnostic Shape Completion
The combined embedding inherits category-agnostic properties from the chosen pretext tasks.
ASFM-Net: Asymmetrical Siamese Feature Matching Network for Point Completion
Yan-Xia/ASFM-Net
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We tackle the problem of object completion from point clouds and propose a novel point cloud completion network employing an Asymmetrical Siamese Feature Matching strategy, termed as ASFM-Net.
Variational Relational Point Completion Network
paul007pl/VRCNet
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CVPR 2021
In particular, we propose a dual-path architecture to enable principled probabilistic modeling across partial and complete clouds.
PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers
In this paper, we present a new method that reformulates point cloud completion as a set-to-set translation problem and design a new model, called PoinTr that adopts a transformer encoder-decoder architecture for point cloud completion.
Voxel-based Network for Shape Completion by Leveraging Edge Generation
xiaogangw/ve-pcn
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ICCV 2021
Deep learning technique has yielded significant improvements in point cloud completion with the aim of completing missing object shapes from partial inputs.
TreeGCN-ED: Encoding Point Cloud using a Tree-Structured Graph Network
Point cloud is one of the widely used techniques for representing and storing 3D geometric data.
