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arXiv 提交日期: 2026-03-08
📄 Abstract - Parameterized Brushstroke Style Transfer

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.

顶级标签: computer vision aigc model training
详细标签: style transfer brushstroke rendering non-photorealistic rendering generative art parameterization 或 搜索:

参数化笔触风格迁移 / Parameterized Brushstroke Style Transfer


1️⃣ 一句话总结

这篇论文提出了一种新的艺术风格迁移方法,它不再像传统方法那样直接修改图像的像素,而是通过模拟真实绘画中的笔触来生成图像,从而获得了更自然、更逼真的艺术效果。

源自 arXiv: 2603.07776