Transfer Learning is an important strategy in Computer Vision to tackle problems the face of limited training data. However, this still heavily depends on amount availabl data, which a challenge for small heritage institutions. This paper investigates various ways enrichingsmaller digital collections boost performance deep learningmodels, using identification musical instruments as case study. ...

In this paper, we focus on a new problem: applying artificial intelligence to automatically generate fashion style images. Given a basic clothing image and a fashion style image (e.g., leopard print), we generate a clothing image with the certain style in real time with a neural fashion style generator. Fashion style generation is related to recent artistic style transfer works, but has its own...

A recent study showed that people evaluate products more positively when they are physically associated with art images than similar non-art images. Neuroimaging studies of visual art have investigated artistic style and esthetic preference but not brain responses attributable specifically to the artistic status of images. Here we tested the hypothesis that the artistic status of images engages...

Which components are needed to identify an object as an artwork, particularly if it is contemporary art? A variety of factors determining aesthetic judgements have been identified, among them stimulus-related properties such as symmetry, complexity and style, but also person-centred as well as context-dependent variables. We were particularly interested in finding out whether laypersons are at ...

Illustrative parallel coordinates (IPC) is a suite of artistic rendering techniques for augmenting and improving parallel coordinate (PC) visualizations. IPC techniques can be used to convey a large amount of information about a multidimensional dataset in a small area of the screen through the following approaches: (a) edge-bundling through splines; (b) visualization of “branched ” clusters to...

Humans comprehend a natural scene at a single glance; painters and other visual artists, through their abstract representations, stressed this capacity to the limit. The performance of computer vision solutions matched that of humans in many problems of visual recognition. In this paper we address the problem of recognizing the genre (subject) in digitized paintings using Convolutional Neural N...