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Neural Style Transfer: A Review [PDF]

IEEE Transactions on Visualization and Computer Graphics, 2020
The seminal work of Gatys et al. demonstrated the power of Convolutional Neural Networks (CNNs) in creating artistic imagery by separating and recombining image content and style. This process of using CNNs to render a content image in different styles is referred to as Neural Style Transfer (NST).
Yongcheng Jing, Yezhou Yang, Zunlei Feng, Jingwen Ye, Yizhou Yu, Mingli Song   +5 more
openaire   +5 more sources

Artistic Style Transfer for Videos [PDF]

, 2016
final version appeared in GCPR-2016; minor changes to improve the ...
Manuel Ruder, Alexey Dosovitskiy, Thomas Brox   +2 more
openaire   +4 more sources

Artistic Arbitrary Style Transfer

CoRR, 2022
12 pages, 7 ...
Weiting Li, Rahul Vyas, Ramya Sree Penta
openaire   +2 more sources

Conversation Style Transfer using Few-Shot Learning [PDF]

, 2023
Conventional text style transfer approaches focus on sentence-level style transfer without considering contextual information, and the style is described with attributes (e.g., formality).
Mansour, Saab, Pappas, Nikolaos, Mansimov, Elman, Roy, Shamik, Shu, Raphael, Roth, Dan, Zhang, Yi   +6 more
core   +1 more source

Cycle consistent style transfer based on style-transition attention [PDF]

Journal of Hebei University of Science and Technology
In order to solve the problem that the existing art style transfer methods can not maintain high-quality image content and transform style patterns at the same time, a novel style-transition attention network (STANet) was introduced, which consists of ...
Rui[DK]’er ZHANG, Xiaohang BIAN, Siyuan LIU, Bin LIU, Jianwu LI, Jun LUO, Mingyue QI   +6 more
doaj   +1 more source

Aesthetic style transferring method based on deep neural network between Chinese landscape painting and classical private garden’s virtual scenario

International Journal of Digital Earth, 2023
Most of the existing virtual scenarios built for the digital protection of Chinese classical private gardens are too modern in expression style to show the aesthetic significance of their historical period.
Shuai Hong, Jie Shen, Guonian Lü, Xiaoyan Liu, Yirui Mao, Nina Sun, Long Tang   +6 more
doaj   +1 more source

Improving zero-shot style transfer text-to-speech by disentangled fine-grained style modeling [PDF]

JASA Express Letters
Recent zero-shot style-transfer speech synthesis methods have shown promising results and addressed adaptation to unseen speaking styles. While most state-of-the-art methods generalize to new speakers and styles using large models or corpora, achieving ...
Eray Eren, Qingju Liu, Abeer Alwan, Gaurav Bharaj   +3 more
doaj   +1 more source

3D Face Arbitrary Style Transfer [PDF]

, 2023
Style transfer of 3D faces has gained more and more attention. However, previous methods mainly use images of artistic faces for style transfer while ignoring arbitrary style images such as abstract paintings.
Zhou, Jiawei, Cai, Yuanhao, Zhao, Chendong, Liu, Zhifang, Liu, Yuxiao, Liu, Yang, Wang, Haoqian, Deng, Xiangwen, Zou, Yingshuang   +8 more
core  

MSSRNet: Manipulating Sequential Style Representation for Unsupervised Text Style Transfer

, 2023
Unsupervised text style transfer task aims to rewrite a text into target style while preserving its main content. Traditional methods rely on the use of a fixed-sized vector to regulate text style, which is difficult to accurately convey the style ...
Zhao, Zhou, Yang, Yazheng, Liu, Qi
core   +1 more source

Style-Content-Aware Adaptive Normalization Based Pose Guided for Person Image Synthesis

IEEE Access, 2023
Most of the tasks based on pose-guided person image synthesis have obtained accurate target pose, but still have not obtained reasonable style texture mapping. In this paper, we propose a new two-stage network to decouple style and content, which aims to
Wei Wei, Xia Yang, Xiaodong Duan, Chen Guo   +3 more
doaj   +1 more source