Results 31 to 40 of about 131,036 (273)

Characterizing and Improving Stability in Neural Style Transfer [PDF]

, 2017
Recent progress in style transfer on images has focused on improving the quality of stylized images and speed of methods. However, real-time methods are highly unstable resulting in visible flickering when applied to videos.
Alahi, Alexandre, Fei-Fei, Li, Gupta, Agrim, Johnson, Justin   +3 more
core   +2 more sources

Style Permutation for Diversified Arbitrary Style Transfer

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, Dan Zhang, Lei Zhao, Duanqing Xu, Dongming Lu   +4 more
doaj   +1 more source

The Intra-Class and Inter-Class Relationships in Style Transfer

Applied Sciences, 2018
Neural style transfer, which has attracted great attention in both academic research and industrial engineering and demonstrated very exciting and remarkable results, is the technique of migrating the semantic content of one image to different artistic ...
Xin Cui, Meng Qi, Yi Niu, Bingxin Li
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

Deep Learning-Based Motion Style Transfer Tools, Techniques and Future Challenges

Sensors, 2023
In the fourth industrial revolution, the scale of execution for interactive applications increased substantially. These interactive and animated applications are human-centric, and the representation of human motion is unavoidable, making the ...
Syed Muhammad Abrar Akber, Sadia Nishat Kazmi, Syed Muhammad Mohsin, Agnieszka Szczęsna   +3 more
doaj   +1 more source

Convolutional Neural Network Style Transfer Towards Chinese Paintings

IEEE Access, 2019
Chinese painting is one of the most important cultural heritages. However, creating a Chinese painting usually requires specific skills, patience, and years of professional training.
Jiachuan Sheng, Caifeng Song, Jun Wang, Yahong Han   +3 more
doaj   +1 more source

Image and Video Style Transfer Based on Transformer

IEEE Access, 2023
The essence of image style transfer is to generate images that both maintain in the original content image and present the effect with artistic features under the guidance of style images.
Sun Fengxue, Sun Yanguo, Lan Zhenping, Wang Yanqi, Zhang Nianchao, Wang Yuru, Li Ping   +6 more
doaj   +1 more source

Augment CAPTCHA Security Using Adversarial Examples With Neural Style Transfer

IEEE Access, 2023
To counteract rising bots, many CAPTCHAs (Completely Automated Public Turing tests to tell Computers and Humans Apart) have been developed throughout the years.
Nghia Dinh, Kiet Tran-Trung, Vinh Truong Hoang   +2 more
doaj   +1 more source

Block Shuffle: A Method for High-Resolution Fast Style Transfer With Limited Memory

IEEE Access, 2020
Fast Style Transfer is a series of Neural Style Transfer algorithms that use feed-forward neural networks to render input images. Because of the high dimension of the output layer, these networks require much memory for computation.
Weifeng Ma, Zhe Chen, Caoting Ji
doaj   +1 more source

Comparing Neural Style Transfer and Gradient-Based Algorithms in Brushstroke Rendering Tasks

Mathematics, 2023
Non-photorealistic rendering (NPR) with explicit brushstroke representation is essential for both high-grade imitating of artistic paintings and generating commands for artistically skilled robots.
Artur Karimov, Ekaterina Kopets, Tatiana Shpilevaya, Evgenii Katser, Sergey Leonov, Denis Butusov   +5 more
doaj   +1 more source