0107-rick

0107-rick's Stars

• junyanz/pytorch-CycleGAN-and-pix2pix

  Image-to-Image Translation in PyTorch

  Language:Python23.3k3481.5k6.3k

• openai/transformer-debugger

  Language:Python4.1k2514241

• Kobaayyy/Awesome-CVPR2024-CVPR2021-CVPR2020-Low-Level-Vision

  A Collection of Papers and Codes for CVPR2024/CVPR2021/CVPR2020 Low Level Vision

  1k321120

• ZhendongWang6/Uformer

  [CVPR 2022] Official implementation of the paper "Uformer: A General U-Shaped Transformer for Image Restoration".

  Language:Python8191181119

• GuoShi28/CBDNet

  Code for "Toward Convolutional Blind Denoising of Real Photographs", CVPR 2019

  Language:Python506134892

• DmitryRyumin/AAAI-2024-Papers

  AAAI 2024 Papers: Explore a comprehensive collection of innovative research papers presented at one of the premier artificial intelligence conferences. Seamlessly integrate code implementations for better understanding. ⭐ experience the forefront of progress in artificial intelligence with this repository!

  Language:Python4728020

• va1shn9v/PromptIR

  PromptIR: Prompting for All-in-One Blind Image Restoration [NeurIPS 2023]

  Language:Python36653827

• nmhkahn/CARN-pytorch

  Fast, Accurate, and Lightweight Super-Resolution with Cascading Residual Network (ECCV 2018)

  Language:Python36595673

• 52CV/ICCV-2023-Papers

  2426412

• submission2019/cnn-quantization

  Quantization of Convolutional Neural networks.

  Language:Python23961960

• codeslake/IFAN

  [CVPR 2021] Official PyTorch Implementation for "Iterative Filter Adaptive Network for Single Image Defocus Deblurring"

  Language:Python22982039

• megvii-research/DCLS-SR

  Official PyTorch implementation of the paper "Deep Constrained Least Squares for Blind Image Super-Resolution", CVPR 2022.

  Language:Python22496220

• hahnyuan/PTQ4ViT

  Post-Training Quantization for Vision transformers.

  Language:Python19532526

• XLearning-SCU/2022-CVPR-AirNet

  PyTorch implementation for All-In-One Image Restoration for Unknown Corruption (AirNet) (CVPR 2022)

  Language:Python17922221

• TencentARC/MM-RealSR

  Codes for "Metric Learning based Interactive Modulation for Real-World Super-Resolution"

  Language:Python15961612

• gy65896/OneRestore

  [ECCV 2024] OneRestore: A Universal Restoration Framework for Composite Degradation

  Language:Python908139

• HDCVLab/Deblurring-by-Realistic-Blurring

  Language:Python632015

• FlyEgle/SDWNet

  [ICCVW2021] An Straight Dilated Network with Wavelet for image Deblurring

  Language:Python60478

• dasongli1/Learning_degradation

  Language:Python581135

• ChangyuanWang17/APQ-DM

  This is the official pytorch implementation for the paper: Towards Accurate Post-training Quantization for Diffusion Models.(CVPR24 Poster Highlight)

  Language:Python34202

• yunhao-zou/RawHDR

  RawHDR: High Dynamic Range Image Reconstruction from a Single Raw Image, ICCV 2023

  27462

• Zj-BinXia/MRDA

  This project is the official implementation of 'Meta-Learning based Degradation Representation for Blind Super-Resolution', TIP2023

  Language:Python27233

• jkhu29/Deblurring-by-Realistic-Blurring

  A PyTorch implementation of the "Deblurring by Realistic Blurring", unofficially

  Language:Python25182

• ZiweiWangTHU/Quantformer

  This is the official pytorch implementation for the paper: *Quantformer: Learning Extremely Low-precision Vision Transformers*.

  Language:Python20113

• ChengxuLiu/DDRNet

  [AAAI2024] Decoupling Degradations with Recurrent Network for Video Restoration in Under-Display Camera.

  Language:Python13121

• vivian210223/arbitrary-scale-blind-SR

  Best of Both Worlds: Learning Arbitrary-scale Blind Super-Resolution via Dual Degradation Representations and Cycle-Consistency (WACV 2024)

  Language:Python11

• XPixelGroup/X-Low-level-Interpretation

  X-Low-Level-Interpretation is dedicated to presenting the research efforts of XPixel in interpretating the principle of neural networks in low-level vision field.

  7102

• mcrl/UDC-SIT

  Language:Jupyter Notebook6212

• Chernobyllight/ReDSR

  Official codes for 'Preserving Full Degradation Details for Blind Image Super-Resolution'

  Language:Python521

• csguoh/llm-course

  Course to get into Large Language Models (LLMs) with roadmaps and Colab notebooks.

  Language:Jupyter Notebook100