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Edge Enhanced Image Style Transfer via Transformers

arXiv 2301.00592 ↗First posted 2 Jan 2023cs.CV eess.IVcited by 0

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Abstract (arXiv)

In recent years, arbitrary image style transfer has attracted more and more attention. Given a pair of content and style images, a stylized one is hoped that retains the content from the former while catching style patterns from the latter. However, it is difficult to simultaneously keep well the trade-off between the content details and the style features. To stylize the image with sufficient style patterns, the content details may be damaged and sometimes the objects of images can not be distinguished clearly. For this reason, we present a new transformer-based method named STT for image style transfer and an edge loss which can enhance the content details apparently to avoid generating blurred results for excessive rendering on style features. Qualitative and quantitative experiments demonstrate that STT achieves comparable performance to state-of-the-art image style transfer methods while alleviating the content leak problem.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 67 of its 82 references that are in the map. First posted on arXiv 2 Jan 2023.

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38 more
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