Parameterized Brushstroke Style Transfer
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Abstract (arXiv)
Computer Vision-based Style Transfer techniques have been used for many years to represent artistic style. However, most contemporary methods have been restricted to the pixel domain; in other words, the style transfer approach has been modifying the image pixels to incorporate artistic style. However, real artistic work is made of brush strokes with different colors on a canvas. Pixel-based approaches are unnatural for representing these images. Hence, this paper discusses a style transfer method that represents the image in the brush stroke domain instead of the RGB domain, which has better visual improvement over pixel-based methods.
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References · 4
- 2021Learning Transferable Visual Models From Natural Language Supervisioncited by 33,456
- 2017Arbitrary Style Transfer in Real-time with Adaptive Instance Normalizationcited by 1,998
- 2018A Style-Aware Content Loss for Real-time HD Style Transfercited by 58
- 2021Rethinking Style Transfer: From Pixels to Parameterized Brushstrokescited by 42
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