Results 61 to 70 of about 5,049,293 (271)
Style Transfer in Text: Exploration and Evaluation
, 2017 Style transfer is an important problem in natural language processing (NLP). However, the progress in language style transfer is lagged behind other domains, such as computer vision, mainly because of the lack of parallel data and principle evaluation ...
Fu, Zhenxin +4 more
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Filter Style Transfer Between Photos [PDF]
, 2020 Over the past few years, image-to-image style transfer has risen to the frontiers of neural image processing. While conventional methods were successful in various tasks such as color and texture transfer between images, none could effectively work with the custom filter effects that are applied by users through various platforms like Instagram.
Yim, Jonghwa +4 more
openaire +2 more sources
ACM SIGKDD Explorations Newsletter, 2022 The stylistic properties of text have intrigued computational linguistics researchers in recent years. Specifically, researchers have investigated the text style transfer task (TST), which aims to change the stylistic properties of the text while retaining its independent content of style.
Hu, Zhiqiang +3 more
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GLStyleNet: exquisite style transfer combining global and local pyramid features
IET Computer Vision, 2020 Recent studies using deep neural networks have shown remarkable success in style transfer, especially for artistic and photo‐realistic images. However, these methods cannot solve more sophisticated problems. The approaches using global statistics fail to
Zhizhong Wang +6 more
doaj +1 more source
Robust Nonparametric Distribution Transfer with Exposure Correction for Image Neural Style Transfer
Sensors, 2020 Image neural style transfer is a process of utilizing convolutional neural networks to render a content image based on a style image. The algorithm can compute a stylized image with original content from the given content image but a new style from the ...
Shuai Liu +3 more
doaj +1 more source
EFANet: Exchangeable Feature Alignment Network for Arbitrary Style Transfer
, 2019 Style transfer has been an important topic both in computer vision and graphics. Since the seminal work of Gatys et al. first demonstrates the power of stylization through optimization in the deep feature space, quite a few approaches have achieved real ...
Gong, Minglun +4 more
core +1 more source
Neural Network Techniques for Image Style Transfer [PDF]
ITM Web of ConferencesWith the rapid advancement of deep learning technology, neural networks have achieved remarkable results in the field of image processing. Particularly in image style transfer, neural network-based methods have become a research hotspot.
Zhang Ziqi
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Coherent Online Video Style Transfer
, 2017 Training a feed-forward network for fast neural style transfer of images is proven to be successful. However, the naive extension to process video frame by frame is prone to producing flickering results. We propose the first end-to-end network for online
Chen, Dongdong +4 more
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CoARF: Controllable 3D Artistic Style Transfer for Radiance Fields [PDF]
International Conference on 3D VisionCreating artistic 3D scenes can be time-consuming and requires specialized knowledge. To address this, recent works such as ARF [57], use a radiance field-based approach with style constraints to generate 3D scenes that resemble a style image provided by
Deheng Zhang +2 more
semanticscholar +1 more source
TET-GAN: Text Effects Transfer via Stylization and Destylization
, 2018 Text effects transfer technology automatically makes the text dramatically more impressive. However, previous style transfer methods either study the model for general style, which cannot handle the highly-structured text effects along the glyph, or ...
Guo, Zongming +3 more
core +1 more source