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

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Geometric Computer Vision Library for Spatial AI

More relighting!

[ECCV 2024] codes of DiffBIR: Towards Blind Image Restoration with Generative Diffusion Prior

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

AIMET is a library that provides advanced quantization and compression techniques for trained neural network models.

A quickstart and benchmark for pytorch distributed training.

PPL Quantization Tool (PPQ) is a powerful offline neural network quantization tool.

CVPR2023 - Activating More Pixels in Image Super-Resolution Transformer Arxiv - HAT: Hybrid Attention Transformer for Image Restoration

Neural Network Compression Framework for enhanced OpenVINO™ inference

Practical Blind Denoising via Swin-Conv-UNet and Data Synthesis (Machine Intelligence Research 2023)

depyf is a tool to help you understand and adapt to PyTorch compiler torch.compile.

[CVPR 2020--Oral] CycleISP: Real Image Restoration via Improved Data Synthesis

PyTorch Image Quality Assessement package

"Denoising Diffusion Models for Plug-and-Play Image Restoration", Yuanzhi Zhu, Kai Zhang, Jingyun Liang, Jiezhang Cao, Bihan Wen, Radu Timofte, Luc Van Gool.

[EMNLP 2024 Industry Track] This is the official PyTorch implementation of "LLMC: Benchmarking Large Language Model Quantization with a Versatile Compression Toolkit".

Neural Network Tools: Converter and Analyzer. For caffe, pytorch, draknet and so on.

[CVPR2021] Invertible Image Signal Processing

[CVPR 2023] Masked Image Training for Generalizable Deep Image Denoising https://arxiv.org/abs/2303.13132

A nnie quantization aware training tool on pytorch.

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

Official codes for DeSRA (ICML 2023)

This is a easy ISP (ez_ISP) for RAW to RGB conversion.

A module to convert pytorch model to caffe model.

pytorch(0.3,0.4) model to caffe