Software and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks

[CVPR 2022 Oral] Official repository for "MAXIM: Multi-Axis MLP for Image Processing". SOTA for denoising, deblurring, deraining, dehazing, and enhancement.

Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time

A Tensorflow implementation of RetinexNet

[ECCV 2020] Learning Enriched Features for Real Image Restoration and Enhancement. SOTA results for image denoising, super-resolution, and image enhancement.

Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.

A PyTorch Implementation of Neural IMage Assessment

Python implementation of "A New Image Contrast Enhancement Algorithm Using Exposure Fusion Framework", CAIP2017

Fast underwater image enhancement for Improved Visual Perception. #TensorFlow #PyTorch #RAL2020

🌕 [BMVC 2022] You Only Need 90K Parameters to Adapt Light: A Light Weight Transformer for Image Enhancement and Exposure Correction. SOTA for low light enhancement, 0.004 seconds try this for pre-processing.

[TPAMI 2022] Learning Enriched Features for Fast Image Restoration and Enhancement. Results on Defocus Deblurring, Denoising, Super-resolution, and image enhancement

Generating RGB photos from RAW image files with PyNET (PyTorch)

Generating RGB photos from RAW image files with PyNET

High-Resolution Image/Video Harmonization [ECCV 2022]

Artificial Intelligence Learning Notes.

[CVPR2023] Blur Interpolation Transformer for Real-World Motion from Blur

[IEEE TIP 2024] DEA-Net: Single image dehazing based on detail-enhanced convolution and content-guided attention

[ECCV 2022] LEDNet: Joint Low-light Enhancement and Deblurring in the Dark

Source code for UWGAN: Underwater GAN for Real-world Underwater Color Restoration and Dehazing

[CVPR 2022 Oral] PyTorch re-implementation for "MAXIM: Multi-Axis MLP for Image Processing", with *training code*. Official Jax repo: https://github.com/google-research/maxim