guochengqian/awesome-self-supervised-learning-on-3D

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guochengqian/awesome-self-supervised-learning-on-3D

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Paper list for anyone who are interested in self-supervised learning on 3D point cloud.

Magic123

[ICLR24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

Jupyter Notebook

PointNeXt

[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies

TENet

[ICCP'22] Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline

openpoints

OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [PointNeXt](https://arxiv.org/abs/2206.04670)

PU-GCN

[CVPR'21] PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks

Pix4Point

Official implementation for [3DV 2024] `Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding`

KAUSTian_Handbook_CN

KAUST Handbook (in Chinese)

ASSANet

[NeurIPS'21 Spotlight] ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning

deep_learning_phd_wiki

Personal use simple handbook for deep learning

tutorial-yaml-wandb

Organize your experiments using yaml and wandb

TNAS

[CVPRW22] Official PyTorch Implementation of "When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search"

ivul_resources

Internal Resources for IVUL members

CS_lifelong_learning

learn c and cpp language

guochengqian

learn_cuda_programming