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
Latest papers
P2C: Self-Supervised Point Cloud Completion from Single Partial Clouds
cuiruikai/partial2complete
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ICCV 2023
Point cloud completion aims to recover the complete shape based on a partial observation.
PG-RCNN: Semantic Surface Point Generation for 3D Object Detection
quotation2520/pg-rcnn
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ICCV 2023
Motivated by this, we propose Point Generation R-CNN (PG-RCNN), a novel end-to-end detector that generates semantic surface points of foreground objects for accurate detection.
SVDFormer: Complementing Point Cloud via Self-view Augmentation and Self-structure Dual-generator
In this paper, we propose a novel network, SVDFormer, to tackle two specific challenges in point cloud completion: understanding faithful global shapes from incomplete point clouds and generating high-accuracy local structures.
Hyperspherical Embedding for Point Cloud Completion
haomengz/hyperpc
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CVPR 2023
Most real-world 3D measurements from depth sensors are incomplete, and to address this issue the point cloud completion task aims to predict the complete shapes of objects from partial observations.
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.
Orthogonal Dictionary Guided Shape Completion Network for Point Cloud
corecai163/ODGNet
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AAAI 2023
Point cloud shape completion, which aims to reconstruct the missing regions of the incomplete point clouds with plausible shapes, is an ill-posed and challenging task that benefits many downstream 3D applications.
3DQD: Generalized Deep 3D Shape Prior via Part-Discretized Diffusion Process
We develop a generalized 3D shape generation prior model, tailored for multiple 3D tasks including unconditional shape generation, point cloud completion, and cross-modality shape generation, etc.
Point Cloud Diffusion Models for Automatic Implant Generation
Advances in 3D printing of biocompatible materials make patient-specific implants increasingly popular.
Parametric Surface Constrained Upsampler Network for Point Cloud
corecai163/pscu
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Designing a point cloud upsampler, which aims to generate a clean and dense point cloud given a sparse point representation, is a fundamental and challenging problem in computer vision.
ACL-SPC: Adaptive Closed-Loop system for Self-Supervised Point Cloud Completion
sangminhong/acl-spc_pytorch
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CVPR 2023
Point cloud completion addresses filling in the missing parts of a partial point cloud obtained from depth sensors and generating a complete point cloud.
