baigeiyingtao

baigeiyingtao's Stars

• Booooooooooo/CSD

  Towards Compact Single Image Super-Resolution via Contrastive Self-distillation, IJCAI21

  Language:Python747

• HobbitLong/RepDistiller

  [ICLR 2020] Contrastive Representation Distillation (CRD), and benchmark of recent knowledge distillation methods

  Language:Python2.2k395

• open-mmlab/mmdeploy

  OpenMMLab Model Deployment Framework

  Language:Python2.7k626

• open-mmlab/mmrazor

  OpenMMLab Model Compression Toolbox and Benchmark.

  Language:Python1.5k227

• clovaai/cutblur

  Rethinking Data Augmentation for Image Super-resolution (CVPR 2020)

  Language:Jupyter Notebook38162

• Fafa-DL/Lhy_Machine_Learning

  李宏毅2021/2022/2023春季机器学习课程课件及作业

  Language:Jupyter Notebook6.1k1.6k

• xinntao/Real-ESRGAN

  Real-ESRGAN aims at developing Practical Algorithms for General Image/Video Restoration.

  Language:Python27.9k3.5k

• cszn/KAIR

  Image Restoration Toolbox (PyTorch). Training and testing codes for DPIR, USRNet, DnCNN, FFDNet, SRMD, DPSR, BSRGAN, SwinIR

  Language:Python2.9k624

• icandle/MAN

  Multi-scale Attention Network for Single Image Super-Resolution (CVPRW 2024)

  Language:Python1117

• yuhuan-wu/P2T

  [TPAMI22] Pyramid Pooling Transformer for Scene Understanding

  Language:Python19818

• workingcoder/EDCNN

  EDCNN: Edge enhancement-based Densely Connected Network with Compound Loss for Low-Dose CT Denoising

  Language:Python14310

• xindongzhang/ELAN

  [ECCV2022] Efficient Long-Range Attention Network for Image Super-resolution

  Language:Python20217

• smitheric95/MoCoViT-PyTorch

  PyTorch implementation of "MoCoViT: Mobile Convolutional Vision Transformer"

  Language:Python172

• microsoft/CSWin-Transformer

  CSWin Transformer: A General Vision Transformer Backbone with Cross-Shaped, CVPR 2022

  Language:Python54278

• MikasaLee/DDPTransformer

  Language:Jupyter Notebook7

• huggingface/pytorch-image-models

  The largest collection of PyTorch image encoders / backbones. Including train, eval, inference, export scripts, and pretrained weights -- ResNet, ResNeXT, EfficientNet, NFNet, Vision Transformer (ViT), MobileNetV4, MobileNet-V3 & V2, RegNet, DPN, CSPNet, Swin Transformer, MaxViT, CoAtNet, ConvNeXt, and more

  Language:Python31.7k4.7k

• wofmanaf/SA-Net

  Code for our ICASSP 2021 paper: SA-Net: Shuffle Attention for Deep Convolutional Neural Networks

  Language:Python24742

• Christian-lyc/NAM

  Language:Python15120

• ZjjConan/SimAM

  The official pytorch implemention of our ICML-2021 paper "SimAM: A Simple, Parameter-Free Attention Module for Convolutional Neural Networks".

  Language:Python40137

• ekojsalim/pengcit-restoration

  Language:Python2

• microsoft/Focal-Transformer

  [NeurIPS 2021 Spotlight] Official code for "Focal Self-attention for Local-Global Interactions in Vision Transformers"

  Language:Python54559

• huawei-noah/Efficient-AI-Backbones

  Efficient AI Backbones including GhostNet, TNT and MLP, developed by Huawei Noah's Ark Lab.

  Language:Python4k700

• damo-cv/ELSA

  The official implementation of ELSA: Enhanced Local Self-Attention for Vision Transformer

  Language:Python11411

• swz30/MPRNet

  [CVPR 2021] Multi-Stage Progressive Image Restoration. SOTA results for Image deblurring, deraining, and denoising.

  Language:Python1.2k190

• shanglianlm0525/CvPytorch

  CvPytorch is an open source COMPUTER VISION toolbox based on PyTorch.

  Language:Python23152

• shanglianlm0525/PyTorch-Networks

  Pytorch implementation of cnn network

  Language:Python1.9k485

• junfu1115/DANet

  Dual Attention Network for Scene Segmentation (CVPR2019)

  Language:Python2.4k483

• yulunzhang/RCAN

  PyTorch code for our ECCV 2018 paper "Image Super-Resolution Using Very Deep Residual Channel Attention Networks"

  Language:Python1.4k314

• wwlCape/HAN

  PyTorch code for our ECCV 2020 paper "Single Image Super-Resolution via a Holistic Attention Network"

  Language:Python16732

• SHI-Labs/Cross-Scale-Non-Local-Attention

  PyTorch code for our paper "Image Super-Resolution with Cross-Scale Non-Local Attention and Exhaustive Self-Exemplars Mining" (CVPR2020).

  Language:Python39946