xiangweigeng

xiangweigeng's Stars

• pytorch/pytorch

  Tensors and Dynamic neural networks in Python with strong GPU acceleration

  Language:Python82.7k1.7k45.5k22.3k

• lencx/ChatGPT

  🔮 ChatGPT Desktop Application (Mac, Windows and Linux)

  Language:Rust52.5k4411.1k5.9k

• open-mmlab/mmdetection

  OpenMMLab Detection Toolbox and Benchmark

  Language:Python29.2k3718.3k9.4k

• tinygrad/tinygrad

  You like pytorch? You like micrograd? You love tinygrad! ❤️

  Language:Python26.4k2737342.9k

• gpakosz/.tmux

  🇫🇷 Oh my tmux! My self-contained, pretty & versatile tmux configuration made with ❤️

  Language:Shell21.9k2506753.4k

• NVlabs/instant-ngp

  Instant neural graphics primitives: lightning fast NeRF and more

  Language:Cuda15.9k2051k1.9k

• facebookresearch/detr

  End-to-End Object Detection with Transformers

  Language:Python13.4k1495262.4k

• karpathy/nn-zero-to-hero

  Neural Networks: Zero to Hero

  Language:Jupyter Notebook11.7k287311.5k

• hua1995116/awesome-ai-painting

  AI绘画资料合集（包含国内外可使用平台、使用教程、参数教程、部署教程、业界新闻等等） Stable diffusion、AnimateDiff、Stable Cascade 、Stable SDXL Turbo

  11.2k12712931

• karpathy/micrograd

  A tiny scalar-valued autograd engine and a neural net library on top of it with PyTorch-like API

  Language:Jupyter Notebook10.1k149301.5k

• open-mmlab/mmcv

  OpenMMLab Computer Vision Foundation

  Language:Python5.8k841.2k1.6k

• open-mmlab/mmdetection3d

  OpenMMLab's next-generation platform for general 3D object detection.

  Language:Python5.2k611.6k1.5k

• fundamentalvision/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.

  Language:Python3.3k69263531

• kwea123/nerf_pl

  NeRF (Neural Radiance Fields) and NeRF in the Wild using pytorch-lightning

  Language:Jupyter Notebook2.7k50209477

• OpenDriveLab/Birds-eye-view-Perception

  [IEEE T-PAMI] Awesome BEV perception research and cookbook for all level audience in autonomous diriving

  Language:Python1.2k3418100

• zhyever/Monocular-Depth-Estimation-Toolbox

  Monocular Depth Estimation Toolbox based on MMSegmentation.

  Language:Python9031597104

• Tsinghua-MARS-Lab/HDMapNet

  Language:Python6862749123

• OpenDriveLab/OpenLane-V2

  [NeurIPS 2023 Track Datasets and Benchmarks] OpenLane-V2: The First Perception and Reasoning Benchmark for Road Driving

  Language:Jupyter Notebook5412110265

• OpenDriveLab/OpenLane

  [ECCV 2022 Oral] OpenLane: Large-scale Realistic 3D Lane Dataset

  Language:C++494187646

• JOP-Lee/READ

  AAAI2023，implementation of "READ: Large-Scale Neural Scene Rendering for Autonomous Driving", the experimental results are significantly better than Nerf-based methods

  Language:Python449216555

• OpenDriveLab/PersFormer_3DLane

  [ECCV 2022 Oral] Perspective Transformer on 3D Lane Detection

  Language:Python4261512577

• Mrmoore98/VectorMapNet_code

  This is the official code base of VectorMapNet (ICML 2023)

  Language:Python401294855

• OpenDriveLab/TCP

  [NeurIPS 2022] Trajectory-guided Control Prediction for End-to-end Autonomous Driving: A Simple yet Strong Baseline.

  Language:Python356126443

• OpenDriveLab/TopoNet

  Topology Reasoning for Scene Perception in Autonomous Driving

  Language:Python271232011

• ybarancan/STSU

  Official code for "Structured Bird’s-Eye-View Traffic Scene Understanding from Onboard Images" (ICCV 2021)

  Language:Python20361923

• valeoai/ALSO

  ALSO: Automotive Lidar Self-supervision by Occupancy estimation

  Language:Python167101019

• YunpengZhai/MEB-Net

  "Multiple Expert Brainstorming for Domain Adaptive Person Re-identification", ECCV 2020

  Language:Python1038817

• ybarancan/TopologicalLaneGraph

  Official implementation of "Topology Preserving Local Road Network Estimation from Single Onboard Camera Image" (CVPR 22)

  Language:Python73769

• YunpengZhai/PEG

  “Population-based Cooperative Gaming for Unsupervised Person Re-identification”, IJCV 2023.

  Language:Python51503

• SeasonDepth/SeasonDepth

  This package provides a python toolkit for the evaluation on the "SeasonDepth: Cross-Season Monocular Depth Prediction Dataset and Benchmark under Multiple Environments", which is also used for SeasonDepth Prediction Challenge, http://seasondepth-challenge.org/.

  Language:Python484105