In this article, we perform an exhaustive analysis of the use of Artificial Neural Networks and Deep Learning in the Visual Arts. We begin by introducing changes in Artificial Intelligence …
Multimodal Large Language Model (MLLM) recently has been a new rising research hotspot, which uses powerful Large Language Models (LLMs) as a brain to perform …
S Li, Y Zhao, R Varma, O Salpekar, P Noordhuis… - arXiv preprint arXiv …, 2020 - arxiv.org
This paper presents the design, implementation, and evaluation of the PyTorch distributed data parallel module. PyTorch is a widely-adopted scientific computing package used in …
Recently style transfer has received a lot of attention. While much of this research has aimed at speeding up the processing, the approaches are still lacking from a principled, art …
This paper provides an overview of some of the most relevant deep learning approaches to pattern extraction and recognition in visual arts, particularly painting and drawing. Recent …
CT has been the central rallying point for K-12 computing education at least since the early 2010s. Many teachers, school administrators, and policymakers have joined the movement …
X Shen, AA Efros, M Aubry - … of the IEEE/CVF conference on …, 2019 - openaccess.thecvf.com
Our goal in this paper is to discover near duplicate patterns in large collections of artworks. This is harder than standard instance mining due to differences in the artistic media (oil …
F Milani, P Fraternali - Journal on Computing and Cultural Heritage …, 2021 - dl.acm.org
Iconography in art is the discipline that studies the visual content of artworks to determine their motifs and themes and to characterize the way these are represented. It is a subject of …
N Garcia, G Vogiatzis - Proceedings of the European …, 2018 - openaccess.thecvf.com
Automatic art analysis has been mostly focused on classifying artworks into different artistic styles. However, understanding an artistic representation involves more complex processes …