guochengqian
Ph.D. candidate@KAUST, B.Eng@XJTU. Interested in 3D vision and 3D Generation
@IVUL-KAUSTThuwal, Saudi Arabia
Pinned Repositories
ASSANet
[NeurIPS'21 Spotlight] ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
KAUSTian_Handbook_CN
KAUST Handbook (in Chinese)
Magic123
[ICLR24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
openpoints
OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [PointNeXt](https://arxiv.org/abs/2206.04670)
Pix4Point
Official implementation for [3DV 2024] `Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding`
PointNeXt
[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
PU-GCN
[CVPR'21] PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks
TENet
[ICCP'22] Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline
deep_gcns_torch
Pytorch Repo for DeepGCNs (ICCV'2019 Oral, TPAMI'2021), DeeperGCN (arXiv'2020) and GNN1000(ICML'2021): https://www.deepgcns.org
AToM
Official implementation of `AToM: Amortized Text-to-Mesh using 2D Diffusion`
guochengqian's Repositories
guochengqian/Magic123
[ICLR24] Official PyTorch Implementation of Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors
guochengqian/PointNeXt
[NeurIPS'22] PointNeXt: Revisiting PointNet++ with Improved Training and Scaling Strategies
guochengqian/openpoints
OpenPoints: a library for easily reproducing point-based methods for point cloud understanding. The engine for [PointNeXt](https://arxiv.org/abs/2206.04670)
guochengqian/TENet
[ICCP'22] Rethinking Learning-based Demosaicing, Denoising, and Super-Resolution Pipeline
guochengqian/PU-GCN
[CVPR'21] PU-GCN: Point Cloud Upsampling using Graph Convolutional Networks
guochengqian/Pix4Point
Official implementation for [3DV 2024] `Pix4Point: Image Pretrained Standard Transformers for 3D Point Cloud Understanding`
guochengqian/KAUSTian_Handbook_CN
KAUST Handbook (in Chinese)
guochengqian/ASSANet
[NeurIPS'21 Spotlight] ASSANet: An Anisotropic Separable Set Abstraction for Efficient Point Cloud Representation Learning
guochengqian/awesome-self-supervised-learning-on-3D
Paper list for anyone who are interested in self-supervised learning on 3D point cloud.
guochengqian/deep_learning_phd_wiki
Personal use simple handbook for deep learning
guochengqian/tutorial-yaml-wandb
Organize your experiments using yaml and wandb
guochengqian/TNAS
[CVPRW22] Official PyTorch Implementation of "When NAS Meets Trees: An Efficient Algorithm for Neural Architecture Search"
guochengqian/ivul_resources
Internal Resources for IVUL members
guochengqian/KPConv-PyTorch-DeepGCN
Kernel Point Convolution implemented in PyTorch
guochengqian/CS_lifelong_learning
learn c and cpp language
guochengqian/deep_gcns_torch
Pytorch Repo for "DeepGCNs: Can GCNs Go as Deep as CNNs?" ICCV2019 Oral https://www.deepgcns.org
guochengqian/guochengqian
guochengqian/learn_cuda_programming
guochengqian/PointCNN
PointCNN: Convolution On X-Transformed Points (NeurIPS 2018)
guochengqian/recommenders
Best Practices on Recommendation Systems
guochengqian/threestudio
A unified framework for 3D content generation.
guochengqian/torch-points3d
Pytorch framework for doing deep learning on point clouds.
guochengqian/BEVFormer
[ECCV 2022] This is the official implementation of BEVFormer, a camera-only framework for autonomous driving perception, e.g., 3D object detection and semantic map segmentation.
guochengqian/bevfusion
BEVFusion: Multi-Task Multi-Sensor Fusion with Unified Bird's-Eye View Representation
guochengqian/CS272-Geometrci-Processing-Curvature-Estimation
Curvature Estimation code for the course project at CS272-Geometrci-Processing
guochengqian/deep-learning-project-template
Pytorch Lightning code guideline for conferences
guochengqian/NeuralRecon
Code for "NeuralRecon: Real-Time Coherent 3D Reconstruction from Monocular Video", CVPR 2021 oral
guochengqian/nvdiffrec
Official code for the CVPR 2022 (oral) paper "Extracting Triangular 3D Models, Materials, and Lighting From Images".
guochengqian/Point-MAE
guochengqian/realfusion