SerdarHelli/diffusion-point-cloud

Model Description

– Luo, Shitong and Hu, Wei – 2021

Proposed a probabilistic generative model for point clouds inspired by non-equilibrium thermodynamics, exploiting the reverse diffusion process to learn the point distribution. All models are available on the original Github repo Link. It consists of a model for airplane model generating.

Documents

• GitHub Repo
• Paper - Diffusion Probabilistic Models for 3D Point Cloud Generation

Datasets

ShapeNet is a comprehensive 3D shape dataset created for research in computer graphics, computer vision, robotics and related diciplines.

• Offical Dataset of ShapeNet
• author's training dataset
• pre-trained models

How to use

Train and test snippets for both auto-encoder and generator are published under the official GitHub repository above.

BibTeX Entry and Citation Info

@inproceedings{luo2021diffusion,
 author = {Luo, Shitong and Hu, Wei},
 title = {Diffusion Probabilistic Models for 3D Point Cloud Generation},
 booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
 month = {June},
 year = {2021}
}