Inharmonious Region Localization by Magnifying Domain Discrepancy
원문 초록
Inharmonious region localization aims to localize the region in a synthetic image which is incompatible with surrounding background. The inharmony issue is mainly attributed to the color and illumination inconsistency produced by image editing techniques. In this work, we tend to transform the input image to another color space to magnify the domain discrepancy between inharmonious region and background, so that the model can identify the inharmonious region more easily. To this end, we present a novel framework consisting of a color mapping module and an inharmonious region localization network, in which the former is equipped with a novel domain discrepancy magnification loss and the latter could be an arbitrary localization network. Extensive experiments on image harmonization dataset show the superiority of our designed framework. Our code is available at https://github.com/bcmi/MadisNet-Inharmonious-Region-Localization.
함께 살펴볼 논문
공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.
DISARM++: Beyond scanner-free harmonization
BIFRÖST: 3D-Aware Image compositing with Language Instructions
FreeCompose: Generic Zero-Shot Image Composition with Diffusion Prior
Training-and-Prompt-Free General Painterly Harmonization via Zero-Shot Disentenglement on Style and Content References
DiffHarmony: Latent Diffusion Model Meets Image Harmonization
IGUANe: a 3D generalizable CycleGAN for multicenter harmonization of brain MR images
토론
이 논문과 연결된 포럼 글이 아직 없습니다.