Point Cloud Completion
75 papers with code • 3 benchmarks • 4 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
Most implemented papers
Multi-View Partial (MVP) Point Cloud Challenge 2021 on Completion and Registration: Methods and Results
Based on the MVP dataset, this paper reports methods and results in the Multi-View Partial Point Cloud Challenge 2021 on Completion and Registration.
Learning Geometric Transformation for Point Cloud Completion
aipixel/GTNet
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International Journal of Computer Vision 2023
It exploits the repetitive geometric structures in common 3D objects to recover the complete shapes, which contains three sub-networks: geometric patch network, structure transformation network, and detail refinement network.
TopNet: Structural Point Cloud Decoder
lynetcha/completion3d
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CVPR 2019
a collection of manifolds or surfaces, for the generated point cloud of a 3D object.
Cascaded Refinement Network for Point Cloud Completion
xiaogangw/cascaded-point-completion
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CVPR 2020
Point clouds are often sparse and incomplete.
GRNet: Gridding Residual Network for Dense Point Cloud Completion
hzxie/GRNet
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ECCV 2020
In particular, we devise two novel differentiable layers, named Gridding and Gridding Reverse, to convert between point clouds and 3D grids without losing structural information.
Detail Preserved Point Cloud Completion via Separated Feature Aggregation
XLechter/Detail-Preserved-Point-Cloud-Completion-via-SFA
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ECCV 2020
In this work, instead of using a global feature to recover the whole complete surface, we explore the functionality of multi-level features and aggregate different features to represent the known part and the missing part separately.
Point Set Voting for Partial Point Cloud Analysis
This paper illustrates that this proposed method achieves state-of-the-art performance on shape classification, part segmentation and point cloud completion.
Point Cloud Completion by Learning Shape Priors
xiaogangw/point-cloud-completion-shape-prior
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Then we learn a mapping to transfer the point features from partial points to that of the complete points by optimizing feature alignment losses.
SoftPoolNet: Shape Descriptor for Point Cloud Completion and Classification
wangyida/softpool
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ECCV 2020
In this paper, we propose a method for 3D object completion and classification based on point clouds.
Cascaded Refinement Network for Point Cloud Completion with Self-supervision
xiaogangw/cascaded-point-completion
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This is to mitigate the dependence of existing approaches on large amounts of ground truth training data that are often difficult to obtain in real-world applications.
