level of abstraction achieved by deep convolutional neural networks as compared to the human performance in the context of paining analysis. To synthesize the motivation, let us recall Pablo Picasso words: ”There is no abstract art. You must always start with something. Afterward you can remove all traces of reality”. Art historians and enthusiasts are able to note, while recalling major artistic works through the history, that the level of abstraction steadily increased.

In parallel, in the last period, works that use computer vision techniques to analyze visual art increased with respect to both the quantity and the quality of reported results. Two trends favored these developments. First, there were consistent efforts to digitize more and more paintings, such that modern systems may learn from large databases. Two of such popular efforts are Your Paintings (now Art UK[^1]) which contains more than 200,000 paintings tightly connected with historical British culture and WikiArt[^2] which contains around 100,000 paintings gathered from multiple national cultures. The databases come with multiple annotations. For this work we are particulary interested in annotations dealing with the painting’s subject or scene type. From this point of view, a more complete database is the WikiArt collection, where the 