This repository hosts ImageCritic, a reference-guided post-editing approach designed to correct inconsistencies in generated images. It aims to solve the inconsistency problem in generated images by applying attention alignment and a detail encoder, providing significant improvements over existing methods in various customized generation scenarios.

The model was presented in the paper The Consistency Critic: Correcting Inconsistencies in Generated Images via Reference-Guided Attentive Alignment.

ImageCritic can effectively resolve detail-related issues in various customized generation scenarios, providing significant improvements over existing methods.

You can try ImageCritic demo on HuggingFace.

If you find this project useful for your research, please consider citing our paper:

If you have any comments or questions, please open a new issue or contact Ziheng Ouyang

Licensed under a Creative Commons Attribution-NonCommercial 4.0 International for Non-commercial use only. Any commercial use should get formal permission first.