The authors propose PHNet, a patch-based normalization network, to address the challenges of harmonizing portraits by focusing on local visual coherence. Their approach showcases state-of-the-art results on the iHarmony4 dataset.
Patch-based normalization network for portrait harmonization achieves state-of-the-art results.
A method is proposed to enable pre-trained latent diffusion models to achieve state-of-the-art results on the image harmonization task by addressing the image distortion issue caused by the VAE compression.