Diverse Image Harmonization
원문 초록
Image harmonization aims to adjust the foreground illumination in a composite image to make it harmonious. The existing harmonization methods can only produce one deterministic result for a composite image, ignoring that a composite image could have multiple plausible harmonization results due to multiple plausible reflectances. In this work, we first propose a reflectance-guided harmonization network, which can achieve better performance with the guidance of ground-truth foreground reflectance. Then, we also design a diverse reflectance generation network to predict multiple plausible foreground reflectances, leading to multiple plausible harmonization results. The extensive experiments on the benchmark datasets demonstrate the effectiveness of our method.
함께 살펴볼 논문
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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
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