Projects sharing features with PerTouch

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)

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)

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