Open-source alternatives to VD Diff

Byeonghyeon Lee, Howoong Lee, Usman Ali, and Eunbyung Park

Diffusion model-based inverse problem solvers have demonstrated state-of-the-art performance in cases where the forward operator is known (i.e. non-blind). However, the applicability of the method to blind inverse problems has yet to be explored. In this work, we show that we can indeed solve a…

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

TOG 2021 Official PyTorch Implementation for "Recurrent Video Deblurring with Blur-Invariant Motion Estimation and Pixel Volumes"

The repository is an official implementation of our CVPR2020 paper : Cascaded Deep Video Deblurring Using Temporal Sharpness Prior

CVPR 2023 - Official DP-NeRF: Deblurred Neural Radiance Field with Physical Scene Priors

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)

Implementation of "Blur-aware Spatio-temporal Sparse Transformer for Video Deblurring". (Zhang et al., CVPR 2024)

Implementation of "Spatio-Temporal Deformable Attention Network for Video Deblurring". (Zhang et al., ECCV 2022)