CuiRuikai

CuiRuikai's Stars

• Anduin2017/HowToCook

  程序员在家做饭方法指南。Programmer's guide about how to cook at home (Simplified Chinese only).

  Language:Dockerfile67.5k4036658.7k

• labmlai/annotated_deep_learning_paper_implementations

  🧑‍🏫 60+ Implementations/tutorials of deep learning papers with side-by-side notes 📝; including transformers (original, xl, switch, feedback, vit, ...), optimizers (adam, adabelief, sophia, ...), gans(cyclegan, stylegan2, ...), 🎮 reinforcement learning (ppo, dqn), capsnet, distillation, ... 🧠

  Language:Python56.3k4581325.8k

• fossasia/visdom

  A flexible tool for creating, organizing, and sharing visualizations of live, rich data. Supports Torch and Numpy.

  Language:Python10k1845611.1k

• arogozhnikov/einops

  Flexible and powerful tensor operations for readable and reliable code (for pytorch, jax, TF and others)

  Language:Python8.5k69180350

• lucidrains/denoising-diffusion-pytorch

  Implementation of Denoising Diffusion Probabilistic Model in Pytorch

  Language:Python8.4k362981k

• huggingface/accelerate

  🚀 A simple way to launch, train, and use PyTorch models on almost any device and distributed configuration, automatic mixed precision (including fp8), and easy-to-configure FSDP and DeepSpeed support

  Language:Python7.9k971.6k967

• heejkoo/Awesome-Score-based-Diffusion-Models

  A collection of resources and papers on Diffusion Models

  Language:HTML7.2k23121589

• facebookresearch/DiT

  Official PyTorch Implementation of "Scalable Diffusion Models with Transformers"

  Language:Python6.3k4481568

• ourongxing/chatgpt-vercel

  Elegant and Powerfull. Powered by OpenAI and Vercel.

  Language:TypeScript3.2k191803k

• pytorch/botorch

  Bayesian optimization in PyTorch

  Language:Jupyter Notebook3.1k52536404

• strawlab/python-pcl

  Python bindings to the pointcloud library (pcl)

  Language:Cython2k56324700

• HuangCongQing/pcl-learning

  🔥PCL（Point Cloud Library）点云库学习记录

  Language:C++1.6k2625398

• erikwijmans/Pointnet2_PyTorch

  PyTorch implementation of Pointnet2/Pointnet++

  Language:Python1.5k17150346

• kuixu/kitti_object_vis

  KITTI Object Visualization (Birdview, Volumetric LiDar point cloud )

  Language:Jupyter Notebook1.1k1551230

• yinyunie/3D-Shape-Analysis-Paper-List

  A list of recent papers, libraries and datasets about 3D shape/scene analysis (by topics, updating).

  Language:Python946812113

• Ovilia/cv

  Wenli Zhang's CV as Web Front-End Engineer

  Language:HTML623647226

• yuxumin/PoinTr

  [ICCV 2021 Oral] PoinTr: Diverse Point Cloud Completion with Geometry-Aware Transformers

  Language:Python62113156111

• dvlab-research/Stratified-Transformer

  Stratified Transformer for 3D Point Cloud Segmentation (CVPR 2022)

  Language:Python37569940

• zekunhao1995/PointFlowRenderer

  Code for rendering the point cloud figures in paper: "PointFlow : 3D Point Cloud Generation with Continuous Normalizing Flows"

  Language:Python3328342

• QhelDIV/ShapeFormer

  Official repository for the ShapeFormer Project

  Language:Python189122322

• ShapeNet/shapenet-viewer

  ShapeNet Viewer

  Language:Scala188153425

• antao97/UnsupervisedPointCloudReconstruction

  Experiments on unsupervised point cloud reconstruction.

  Language:Python1657927

• princeton-vl/SimpleView

  Official Code for ICML 2021 paper "Revisiting Point Cloud Shape Classification with a Simple and Effective Baseline"

  Language:Python155101523

• yinyunie/depth_renderer

  Rendering color and depth images for ShapeNet models.

  Language:Python863920

• haotian-liu/MaskPoint

  [ECCV 2022] Masked Discrimination for Self-Supervised Learning on Point Clouds

  Language:Python85885

• JingZhang617/UncertaintyEstimation

  Language:Python49326

• yuchenrao/PatchComplete

  This is the official code for "Learning Multi-Resolution Patch Priors for 3D Shape Completion on Unseen Categories"

  Language:Python461102

• cdphelan/bayesian-template

  This repo is a set of templates that will guide you through a Bayesian analysis in R, even if you have never done Bayesian analysis before. The research paper that accompanies these templates is forthcoming at CHI 2019: "Some Prior(s) Experience Necessary: Templates for Getting Started in Bayesian Analysis."

  Language:HTML17508

• LIVIAETS/extended_logbarrier

  Code for our arxiv preprint: https://arxiv.org/abs/1904.04205

  Language:Python13302

• ljxw88/contrastive-notes

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