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Previous research has shown that Artificial Intelligence is capable of distinguishing between authentic paintings by a given artist and human-made forgeries with remarkable accuracy, provided sufficient training. However, with the limited amount of existing known forgeries, augmentation methods for forgery detection are highly desirable. In this work, we examine the potential of incorporating synthetic artworks into training datasets to enhance the performance of forgery detection. Our investigation focuses on paintings by Vincent van Gogh, for which we release the first dataset specialized for forgery detection. To reinforce our results, we conduct the same analyses on the artists Amedeo Modigliani and Raphael. We train a classifier to distinguish original artworks from forgeries. For this, we use human-made forgeries and imitations in the style of well-known artists and augment our training sets with images in a similar style generated by Stable Diffusion and StyleGAN. We find that the additional synthetic forgeries consistently improve the detection of human-made forgeries. In addition, we find that, in line with previous research, the inclusion of synthetic forgeries in the training also enables the detection of AI-generated forgeries, especially if created using a similar generator. [ABSTRACT FROM AUTHOR]

Claude Debussy's personal style is typically characterised as a departure from earlier diatonic tonality, including a greater variety of pitch-class materials organised in fragmented yet coherent compositions. Exploiting the music-theoretical interpretability of Discrete Fourier Transforms over pitch-class distributions, we performed a corpus study over Debussy's solo-piano works in order to investigate the diachronic development of such stylistic features across the composer's lifespan. We propose quantitative heuristics for the prevalence of different pitch-class prototypes, the fragmentation of a piece across different prototypes, as well as some aspect of the overall coherence of a piece. We found strong evidence for a decrease of diatonicity in favour of octatonicity, as well as for an increase of fragmentation accompanied by non-decreasing coherence. These results contribute to the understanding of the historical development of extended-tonal harmony, while representing a fertile testing ground for the interaction of computational corpus-based methods with traditional music analytical approaches. [ABSTRACT FROM AUTHOR]

Designing a novel approach to existing art collections requires a shift in perspective. Computational approaches allow for an agnostic approach to cultural assets--akin to distant reading--,affording a capacity for embracing estrangement as a fertile design strategy. This paper investigates the potential convergence of these fields through the lens of machine curation and audience engagement, specifically examining the influence of contemporary machine learning models on curatorial methodologies. This investigation takes the form of a project conceived for the 2023 Helsinki Art Biennial and as a collaboration between the Centre for Digital Visual Studies (MPG, University of Zurich) and the media artist Yehwan Song, aptly titled Newly Formed City. Exploring the art collection of the Helsinki Art Museum (HAM), we seek to reinterpret the cityscape of Helsinki through a machine-oriented perspective. Utilising visual-textual models, we relocate unexhibited artworks to public locations, where, through the creation of context-based computer generated 360-degree panoramas, artworks are placed. Consequently, the outdoor sites are changed by the presence of the artworks, creating a new speculative geography where the city and its art collection are visually fused together. Interaction is achieved through a web interface, offering visitors the opportunity to move through an alternative version of the city and interact with its cultural heritage on a large scale, exploring the capacities for creativity located at the crossroads of a reflective exchange between vicinity and ignorance, machinic analytical prowess, and the uncanny and the unexpected. [ABSTRACT FROM AUTHOR]