Technologies related to artificial intelligence (AI) have a strong impact on the changes of
research and creative practices in visual arts. The growing number of research initiatives …

The aim of this paper is to give an overview of domain adaptation and transfer learning with
a specific view on visual applications. After a general motivation, we first position domain …

“Ceci n'est pas une pipe” French for “This is not a pipe”. This is the description painted on
the first painting in the figure above. But to most of us, how could this painting is not a pipe …

Automatic art analysis has been mostly focused on classifying artworks into different artistic
styles. However, understanding an artistic representation involves more complex processes …

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 …

This work introduces a dataset for large-scale instance-level recognition in the domain of
artworks. The proposed benchmark exhibits a number of different challenges such as large …

Answering questions related to art pieces (paintings) is a difficult task, as it implies the
understanding of not only the visual information that is shown in the picture, but also the …

Visual narrative is often a combination of explicit information and judicious omissions,
relying on the viewer to supply missing details. In comics, most movements in time and …

The objective of this work is to find objects in paintings by learning object-category
classifiers from available sources of natural images. Finding such objects is of much benefit …

Real-world applications of computer vision in the humanities require algorithms to be robust
against artistic abstraction, peripheral objects, and subtle differences between fine-grained …