目录
Resolution_Image_Harmonization_via_Collaborative_Dual_Transformations_CVPR_2022_paper
Target
image harmonization aims to adjust the foreground to make it compatible with the background.
Problem:
Conventional image harmonization methods learn global RGB-to-RGB transformation which could effort lessly scale to high resolution, but ignore diverse local context. Recent deep learning methods learn the dense pixel-to-pixel transformation which could generate harmonious outputs, but are highly constrained in low resolution.
This paper:
High-resolution image harmonization network with Collaborative Dual Transformation (CDTNet) to combine pixel-to-pixel transformation and RGB-to-RGB transformation coherently in an end-to-end network.
Contribution:
- We unify pixel-to-pixel transforma

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