Progressive Painterly Image Harmonization from Low-Level Styles to High-Level Styles
Li Niu,
Yan Hong,
Junyan Cao
et al.
Abstract:Painterly image harmonization aims to harmonize a photographic foreground object on the painterly background. Different from previous auto-encoder based harmonization networks, we develop a progressive multi-stage harmonization network, which harmonizes the composite foreground from low-level styles (e.g., color, simple texture) to high-level styles (e.g., complex texture). Our network has better interpretability and harmonization performance. Moreover, we design an early-exit strategy to automatically decide … Show more
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