tjussh

AdderNet

Code for paper " AdderNet: Do We Really Need Multiplications in Deep Learning?"

ADNet

Pytorch implementation of ADNet. (The winning method of the first edition of NTIRE2021 Multi-Frame HDR Challenge)

ArbSR

[ICCV 2021] Learning A Single Network for Scale-Arbitrary Super-Resolution

bpn

CF-Net

Official repository of "Deep Coupled Feedback Network for Joint Exposure Fusion and Image Super-Resolution"

Component-Divide-and-Conquer-for-Real-World-Image-Super-Resolution

d2l-zh

《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被60多个国家的400多所大学用于教学。

DCNv2

Deformable Convolutional Networks v2 with Pytorch

DeepFaceLive

DeepHDRVideo

HDR Video Reconstruction: A Coarse-to-fine Network and A Real-world Benchmark Dataset (ICCV 2021)

fast-openISP

fast-openISP: a faster re-implementation of openISP

focal-frequency-loss

[ICCV 2021] Focal Frequency Loss for Image Reconstruction and Synthesis

ImageProcessing-Python

该资源为作者在CSDN的撰写Python图像处理文章的支撑，主要是Python实现图像处理、图像识别、图像分类等算法代码实现，希望该资源对您有所帮助，一起加油。

imgaug

Image augmentation for machine learning experiments.

InvDN

Implementation for the paper: Invertible Denoising Network: A Light Solution for Real Noise Removal (CVPR2021).

Invertible-ISP

[CVPR2021] Invertible Image Signal Processing

Jalali-Lab-Implementation-of-RAISR

Implementation of RAISR (Rapid and Accurate Image Super Resolution) algorithm in Python 3.x by Jalali Laboratory at UCLA. The implementation presented here achieved performance results that are comparable to that presented in Google's research paper (with less than ± 0.1 dB in PSNR). Just-in-time (JIT) compilation employing JIT numba is used to speed up the Python code. A very parallelized Python code employing multi-processing capabilities is used to speed up the testing process. The code has been tested on GNU/Linux and Mac OS X 10.13.2 platforms.

KAIR

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

LDL

Official implementation of the paper 'Details or Artifacts: A Locally Discriminative Learning Approach to Realistic Image Super-Resolution' in CVPR 2022

NBNet

Pytorch implement "NBNet: Noise Basis Learning for Image Denoising with Subspace Projection"

openISP

Image Signal Processor

Pretrained-IPT

pytorch-loss-functions

A collection of loss functions with easy usage

pytorch-receptive-field

Compute CNN receptive field size in pytorch in one line

raisr

A Python implementation of RAISR

sr_mobile_pytorch

A PyTorch port of `NJU-Jet/SR_Mobile_Quantization`

SR_Mobile_Quantization

Winner solution of mobile AI (CVPRW 2021).

traiNNer

traiNNer: Deep learning framework for image and video super-resolution, restoration and image-to-image translation, for training and testing.

vit-pytorch

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

XLSR

PyTorch implementation of paper "Extremely Lightweight Quantization Robust Real-Time Single-Image Super Resolution for Mobile Devices"