Results 11 to 20 of about 5,049,293 (271)
Inversion-based Style Transfer with Diffusion Models [PDF]
Computer Vision and Pattern Recognition, 2022 The artistic style within a painting is the means of expression, which includes not only the painting material, colors, and brushstrokes, but also the high-level attributes, including semantic elements and object shapes. Previous arbitrary example-guided
Yu-xin Zhang +6 more
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Structure-Preserving Neural Style Transfer [PDF]
IEEE Transactions on Image Processing, 2020 State-of-the-art neural style transfer methods have demonstrated amazing results by training feed-forward convolutional neural networks or using an iterative optimization strategy. The image representation used in these methods, which contains two components: style representation and content representation, is typically based on high-level features ...
Cheng, Ming-Ming +5 more
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Style Transfer of Thangka Images Highlighting Style Attributes
IEEE Access, 2023 The HAA-GAN (Highlighting Artistic Attributes Generative Adversarial Net-work) style migration model is proposed to address the problem of poor expression of image artistic attributes and mismatch between semantic and stylistic features in images ...
Wenjin Hu +4 more
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Image Style Transfer via Multi-Style Geometry Warping
Applied Sciences, 2022 Style transfer of an image has been receiving attention from the scientific community since its inception in 2015. This topic is characterized by an accelerated process of innovation; it has been defined by techniques that blend content and style, first ...
Ioana Alexandru +6 more
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Photorealistic Style Transfer Guided by Global Information [PDF]
Jisuanji kexue, 2022 Different from artistic style transfer,the challenge of photorealistic style transfer is to maintain the authenticity of the output while transferring the color style of the style input.Now,most photorealistic style transfer methods perform pre-proces ...
ZHANG Ying-tao, ZHANG Jie, ZHANG Rui, ZHANG Wen-qiang
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Arbitrary Style Transfer in Real-Time with Adaptive Instance Normalization [PDF]
IEEE International Conference on Computer Vision, 2017 Gatys et al. recently introduced a neural algorithm that renders a content image in the style of another image, achieving so-called style transfer.
Xun Huang, Serge J. Belongie
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Domain Enhanced Arbitrary Image Style Transfer via Contrastive Learning [PDF]
International Conference on Computer Graphics and Interactive Techniques, 2022 In this work, we tackle the challenging problem of arbitrary image style transfer using a novel style feature representation learning method. A suitable style representation, as a key component in image stylization tasks, is essential to achieve ...
Yu-xin Zhang +6 more
semanticscholar +1 more source
Exact Feature Distribution Matching for Arbitrary Style Transfer and Domain Generalization [PDF]
Computer Vision and Pattern Recognition, 2022 Arbitrary style transfer (AST) and domain generalization (DG) are important yet challenging visual learning tasks, which can be cast as a feature distribution matching problem.
Yabin Zhang +4 more
semanticscholar +1 more source
Coarse-to-Fine Structure-Aware Artistic Style Transfer
Applied Sciences, 2023 Artistic style transfer aims to use a style image and a content image to synthesize a target image that retains the same artistic expression as the style image while preserving the basic content of the content image. Many recently proposed style transfer
Kunxiao Liu +3 more
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Arbitrary Style Transfer With Style-Attentional Networks [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Arbitrary style transfer aims to synthesize a content image with the style of an image to create a third image that has never been seen before. Recent arbitrary style transfer algorithms find it challenging to balance the content structure and the style patterns.
Park, Dae Young, Lee, Kwang Hee
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