Projects sharing features with Difflid

The code and pre-trained models of the paper "Image Deblurring based on Diffusion Models" will be released in this repository.

Jiezhang Cao, Yue Shi, Kai Zhang, Yulun Zhang, Radu Timofte, Luc Van Gool

Official implementation of Paper "Rethinking Video Deblurring with Wavelet-Aware Dynamic Transformer and Diffusion Model" (ECCV 2024)

CVPR 2025 Reconciling Stochastic and Deterministic Strategies for Zero-shot Image Restoration using Diffusion Model in Dual, PyTorch Implementation

Image restoration for fluorescence microscopy

NeurIPS2024 Overcome hallucination of diffusion restoration models.

Official implementation of "Text-Aware Image Restoration with Diffusion Models"

A Python toolbox for quantitative, reproducible flow cytometry analysis

Official code for Zero-Reference Low-Light Enhancement via Physical Quadruple Priors (CVPR-24)

CVPR 2024 oralThis repository contains the official implementation of "FlowIE: Efficient Image Enhancement via Rectified Flow"

This is the official implementation of InstaRevive: One-Step Image Enhancement via Dynamic Score Matching

SUPIR is an AI image upscaler and restoration system designed to remove artifacts and restore quality to real-world photographs. It functions as a diffusion-based image enhancer and restoration tool that uses large-scale model scaling to produce high-resolution results with photorealistic details. The system balances visual aesthetics with input fidelity, allowing for a trade-off between strict adherence to the original image and the overall visual appeal of the output. It leverages large-scale model inference to improve image clarity and maintain realistic details during the upscaling proces

[Paper](https://arxiv.org/abs/2304.01247) [Project Page](https://generativediffusionprior.github.io/)

(† Co-first Author, Corresponding Author)

ICCV 2025 FoundIR: Unleashing Million-scale Training Data to Advance Foundation Models for Image Restoration

NeurIPS2024: Diffusion Priors for Variational Likelihood Estimation and Image Denoising

GenDR: Lightning Generative Detail Restorator

SeedVR2: One-Step Video Restoration via Diffusion Adversarial Post-Training

This is the code repository of the following paper to train and perform inference with patch-based diffusion models for image restoration under adverse weather conditions.

Project Page | Paper | Personal HomePage

Paper | Project

1.Sichuan University, 2.Southwest Jiaotong University, 3.University of Electronic Science and Technology of China, 4.Shanghai Jiaotong University, 5.Megvii Technology

Official PyTorch implementation for "Learning to See in the Extremely Dark"

ACM MM 2025 Enhancing Diffusion Model Stability for Image Restoration via Gradient Management