Gordon (Guocheng) Qian

Magic123. [ICLR'24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors

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

openpoints. OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [ASSANet](https://arxiv.org/abs/2110.10538), [PointNeXt](https://arxiv.org/abs/2206.04670)

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

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

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

tutorial-yaml-wandb. Organize your experiments using yaml and wandb

deep_learning_phd_wiki. Personal use simple handbook for deep learning

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

ivul_resources. Internal Resources for IVUL members

KPConv-PyTorch-DeepGCN. Kernel Point Convolution implemented in PyTorch

threestudio. A unified framework for 3D content generation.

torch-points3d. Pytorch framework for doing deep learning on point clouds.

second.pytorch. SECOND for KITTI/NuScenes object detection

learn_cuda_programming.

n2v. This is the implementation of Noise2Void training.

CS_lifelong_learning. learn c and cpp language

guochengqian.

PointCNN. PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)

pt.darts. PyTorch Implementation of DARTS: Differentiable Architecture Search

deep_gcns_torch. Pytorch Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?" ICCV2019 Oral https://www.deepgcns.org

CS380-GPGPU_Programming-OpenGL. OpenGL projects (course CS380 at KAUST)

recommenders. Best Practices on Recommendation Systems