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arXiv 1805.03857cs.CV

Avatar-Net: Multi-scale Zero-shot Style Transfer by Feature Decoration

The Chinese University of Hong Kong(香港中文大学);SenseTime Research(商汤科技研究院);CUHK-SenseTime Joint Lab(香港中文大学-商汤科技联合实验室)

Lu Sheng, Ziyi Lin, Jing Shao, Xiaogang Wang

英文摘要:

Zero-shot artistic style transfer is an important image synthesis problem aiming at transferring arbitrary style into content images. However, the trade-off between the generalization and efficiency in existing methods impedes a high quality zero-shot style transfer in real-time. In this paper, we resolve this dilemma and propose an efficient yet effective Avatar-Net that enables visually plausible multi-scale transfer for arbitrary style. The key ingredient of our method is a style decorator that makes up the content features by semantically aligned style features from an arbitrary style image, which does not only holistically match their feature distributions but also preserve detailed style patterns in the decorated features. By embedding this module into an image reconstruction network that fuses multi-scale style abstractions, the Avatar-Net renders multi-scale stylization for any style image in one feed-forward pass. We demonstrate the state-of-the-art effectiveness and efficiency of the proposed method in generating high-quality stylized images, with a series of applications include multiple style integration, video stylization and etc.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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