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
Latest papers with no code
3DMambaComplete: Exploring Structured State Space Model for Point Cloud Completion
Point cloud completion aims to generate a complete and high-fidelity point cloud from an initially incomplete and low-quality input.
Zero-shot Point Cloud Completion Via 2D Priors
3D point cloud completion is designed to recover complete shapes from partially observed point clouds.
3D Object Detection and High-Resolution Traffic Parameters Extraction Using Low-Resolution LiDAR Data
These are the need for multiple LiDAR systems to obtain complete point cloud information of objects of interest, as well as the labor-intensive process of annotating 3D bounding boxes for object detection tasks.
P2M2-Net: Part-Aware Prompt-Guided Multimodal Point Cloud Completion
Inferring missing regions from severely occluded point clouds is highly challenging.
BonnBeetClouds3D: A Dataset Towards Point Cloud-based Organ-level Phenotyping of Sugar Beet Plants under Field Conditions
Agricultural production is facing severe challenges in the next decades induced by climate change and the need for sustainability, reducing its impact on the environment.
Three-Filters-to-Normal+: Revisiting Discontinuity Discrimination in Depth-to-Normal Translation
This article introduces three-filters-to-normal+ (3F2N+), an extension of our previous work three-filters-to-normal (3F2N), with a specific focus on incorporating discontinuity discrimination capability into surface normal estimators (SNEs).
Rotation-Invariant Completion Network
To assess the performance of RICNet and existing methods on point clouds with various poses, we applied random transformations to the point clouds in the MVP dataset and conducted experiments on them.
Fine-grained Text and Image Guided Point Cloud Completion with CLIP Model
In this work, we propose a novel multimodal fusion network for point cloud completion, which can simultaneously fuse visual and textual information to predict the semantic and geometric characteristics of incomplete shapes effectively.
High-Resolution Cranial Defect Reconstruction by Iterative, Low-Resolution, Point Cloud Completion Transformers
The problem of the automatic cranial defect reconstruction can be formulated as the shape completion task and solved using dedicated deep networks.
Multi-class point cloud completion networks for 3D cardiac anatomy reconstruction from cine magnetic resonance images
Cine magnetic resonance imaging (MRI) is the current gold standard for the assessment of cardiac anatomy and function.
