EditHF-1M: A Million-Scale Rich Human Preference Feedback for Image Editing

ArXi:2603.14916v1 Announce Type: new Recent text-guided image editing (TIE) models have achieved remarkable progress, while many edited images still suffer from issues such as artifacts, unexpected editings, unaesthetic contents. Although some benchmarks and methods have been proposed for evaluating edited images, scalable evaluation models are still lacking, which limits the development of human feedback reward models for image editing. To address the challenges, we first