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2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 'Style transfer' among images has recently emerged as a very active research topic, fuelled by the power of convolution neural networks (CNNs), and has become fast a very popular technology in social media.
Duong, Ngoc +3 more
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Style Permutation for Diversified Arbitrary Style Transfer [PDF]
IEEE Access, 2020 Arbitrary neural style transfer aims to render a content image in a randomly given artistic style using the features extracted from a well-trained convolutional neural network.
Pan Li +4 more
doaj +2 more sources
Style-NeRF2NeRF: 3D Style Transfer from Style-Aligned Multi-View Images [PDF]
SIGGRAPH Asia 2024 Conference PapersWe propose a simple yet effective pipeline for stylizing a 3D scene, harnessing the power of 2D image diffusion models. Given a NeRF model reconstructed from a set of multi-view images, we perform 3D style transfer by refining the source NeRF model using
Haruo Fujiwara +2 more
semanticscholar +3 more sources
International Journal for Research in Applied Science and Engineering Technology: The Basically [NST] means a Neural Style Transfer is one Model for changing the whole behaviour of the images. Through the NST we can create a multiple new images using a multiple content image and multiple style images, through this model we can ...
Dhawade Sarika
semanticscholar +3 more sources
Authorship style transfer with inverse transfer data augmentation
AI OpenAuthorship style transfer aims to modify the style of neutral text to match the unique speaking or writing style of a particular individual. While Large Language Models (LLMs) present promising solutions, their effectiveness is limited by the small ...
Zhonghui Shao +8 more
doaj +2 more sources
Arbitrary Image Style Transfer with Consistent Semantic Style [PDF]
Jisuanji kexue, 2023 The goal of image style transfer is to synthesize an output image by transferring the style of the target image to a given content image.There are a large number of image style transfer works,but the stylization results ignore the manifold distribution ...
YAN Mingqiang, YU Pengfei, LI Haiyan, LI Hongsong
doaj +1 more source
Style Injection in Diffusion: A Training-Free Approach for Adapting Large-Scale Diffusion Models for Style Transfer [PDF]
Computer Vision and Pattern Recognition, 2023 Despite the impressive generative capabilities of diffusion models, existing diffusion model-based style transfer methods require inference-stage optimization (e.g.
Jiwoo Chung, Sangeek Hyun, Jae-Pil Heo
semanticscholar +1 more source
AdaAttN: Revisit Attention Mechanism in Arbitrary Neural Style Transfer [PDF]
IEEE International Conference on Computer Vision, 2021 Fast arbitrary neural style transfer has attracted widespread attention from academic, industrial and art communities due to its flexibility in enabling various applications. Existing solutions either attentively fuse deep style feature into deep content
Songhua Liu +8 more
semanticscholar +1 more source
StyTr2: Image Style Transfer with Transformers [PDF]
Computer Vision and Pattern Recognition, 2021 The goal of image style transfer is to render an image with artistic features guided by a style reference while maintaining the original content. Owing to the locality in convolutional neural networks (CNNs), extracting and maintaining the global ...
Yingying Deng +6 more
semanticscholar +1 more source
CLIPstyler: Image Style Transfer with a Single Text Condition [PDF]
Computer Vision and Pattern Recognition, 2021 Existing neural style transfer methods require reference style images to transfer texture information of style images to content images. However, in many practical situations, users may not have reference style images but still be inter-ested in ...
Gihyun Kwon, Jong-Chul Ye
semanticscholar +1 more source