Art theft has become a major problem in the world of Non-Fungible Tokens (NFTs) as grifters look to make a quick buck from the works of others. The nature of the online goods means it's very difficult to confirm who owns the NFTs being sold and if the sellers have the legal right to sell that work on any platform. Progress on a solution has been slow, but it does appear new tactics from hosting companies like DeviantArt are working. DeviantArt recently implemented a new system designed to help identify stolen artwork in the wild by using machine learning to locate works that may have been stolen. It's even able to detect subtle variations in stolen artwork, including if an image is cropped, flipped or slightly altered to avoid traditional image detection systems.
Sartori, Andreza (University of Trento and Telecom Italia) | Yan, Yan (University of Trento and UIUC, Singapore) | Özbal, Gözde (Fondazione Bruno Kessler) | Salah, Alkim Almila Akdag (Royal Netherlands Academy of Arts and Sciences) | Salah, Albert Ali (Boğaziçi University) | Sebe, Nicu (University of Trento)
Abstract artists use non-figurative elements (i.e. colours, lines, shapes, and textures) to convey emotions and often rely on the titles of their various compositions to generate (or enhance) an emotional reaction in the audience. Several psychological works observed that the metadata (i.e., titles, description and/or artist statements) associated with paintings increase the understanding and the aesthetic appreciation of artworks. In this paper we explore if the same metadata could facilitate the computational analysis of artworks, and reveal what kind of emotional responses they awake. To this end, we employ computer vision and sentiment analysis to learn statistical patterns associated with positive and negative emotions on abstract paintings. We propose a multimodal approach which combines both visual and metadata features in order to improve the machine performance. In particular, we propose a novel joint flexible Schatten p-norm model which can exploit the sharing patterns between visual and textual information for abstract painting emotion analysis. Moreover, we conduct a qualitative analysis on the cases in which metadata help improving the machine performance.
To celebrate Sonic the Hedgehog's 26th birthday this summer, Anippon teamed up with Sega to create some Sonic-inspired shoes for all the fans who took one look at Sonic's classic red and white shoes and thought, "I need those." The shoes cost about $60, which honestly isn't a terrible price, but you could do so much better than these shoes. Sonic fans have been creating their own, better versions of these Anippon shoes for years. SEE ALSO: Tons of classic Sega games are coming to your phone (for free!) First of all, if you truly want to emulate the world's fastest blue hedgehog you probably shouldn't be sprinting around in faux-leather loafers. What you should be wearing are these custom Jordans.
Wang, Xin (Simon Fraser University) | Donaldson, Roger (The University of British Columbia) | Nell, Christopher (DeviantArt, Inc.) | Gorniak, Peter (DeviantArt, Inc.) | Ester, Martin (Simon Fraser University) | Bu, Jiajun (Zhejiang University)
Social networks often provide group features to help users with similar interests associate and consume content together. Recommending groups to users poses challenges due to their complex relationship: user-group affinity is typically measured implicitly and varies with time; similarly, group characteristics change as users join and leave. To tackle these challenges, we adapt existing matrix factorization techniques to learn user-group affinity based on two different implicit engagement metrics: (i) which group-provided content users consume; and (ii) which content users provide to groups. To capture the temporally extended nature of group engagement we implement a time-varying factorization. We test the assertion that latent preferences for groups and users are sparse in investigating elastic-net regularization. Experiments using data from DeviantArt indicate that the time-varying implicit engagement-based model provides the best top-K group recommendations, illustrating the benefit of the added model complexity.
Many a mash-up have impressed the Internet masses -- from Disney-themed reimaginings to all things Potter World. Now, Abraham Perez has taken a retired girl squad into space. Perez, who goes by SparkleArmy in the artist forum DeviantArt, brought together two favorites, Golden Girls plus Sailor Moon, to create some powerhouse art with attitude. Perez hones in on a girl-power sensibility to combine the dry wit of the Florida Foursome with the equally empowering anime supergirls. The series titled Beautiful Guardians Golden Girls is both artistically uplifting and sassy.