Abstract:Image harmonization is a critical task in computer vision, which aims to adjust the fore-ground to make it compatible with the back-ground. Recent works mainly focus on using global transformation (i.e., normalization and color curve rendering) to achieve visual consistency. However, these model ignore local consistency and their model size limit their harmonization ability on edge devices. Inspired by the dynamic deep networks that adapt the model structures or parameters conditioned on the inputs, we propose… Show more
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