In this work, we propose a new feed-forward arbitrary style transfer method, referred to as
StyleFormer, which can simultaneously fulfill fine-grained style diversity and semantic …

A style mapper applies some fixed style to its input images (so, for example, taking faces to
cartoons). This paper describes a simple procedure–JoJoGAN–to learn a style mapper from …

Machine learning models, especially deep neural networks (DNNs), have been shown to be
vulnerable against adversarial examples which are carefully crafted samples with a small …

This paper proposes two new data augmentation approaches based on Deep Convolutional
Generative Adversarial Networks (DCGANs) and Style Transfer for augmenting Parkinson's …

Image style transfer (IST) has drawn broad attention recently. At present, convolutional
neural network (CNN)-based methods and generative adversarial network (GAN)-based …

Style transfer is a well-known approach used to transfer the art style of a style image to an
input content image, and the core method of the style transfer is to use the Gram matrix for …

图像风格迁移是计算机视觉领域的一个热点研究方向. 随着深度学习的兴起,
图像风格迁移领域得到了突破性的发展. 为了推进图像风格迁移领域的发展 …

Computational art analysis has, through its reliance on classification tasks, prioritised
historical datasets in which the artworks are already well sorted with the necessary …

In this paper, we demonstrate the vulnerabilities of learning-based algorithms for perception-
based autonomy as applied to unmanned aerial systems (UAS). We present an attack …

ABSTRACT Neural Style Transfer (NST) has been a widely researched topic as of late
enabling new forms of image manipulation. Here we perform an extensive study on NST …