What is it about?
The paper introduces an automatic architecture for portrait stylization. Given limited style exemplars (∼100), the new architecture can produce high-quality style transfer results with advanced ability to synthesize high-fidelity contents, strong generality to handle complicated scenes (e.g., occlusions and accessories), and high scalability to full-body translation with only head observations.
Photo by Timon Klauser on Unsplash
Why is it important?
We define the new rule of "calibration first, translation later" for few-shot image translation task, and explore the augmented global structure with locally-focused translation. This elegant design makes all-around quality boosts compared with previous methods.
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This page is a summary of: DCT-net, ACM Transactions on Graphics, July 2022, ACM (Association for Computing Machinery), DOI: 10.1145/3528223.3530159.
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