AI Art Curation: Re-imagining the city of Helsinki in occasion of its Biennial

Authors: Ludovica Schaerf, Pepe Ballestreros, Valentine Bernasconi, Iacopo Neri, Dario Neguerela del Castillo (2023)

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Abstract: Art curatorial practice is characterized by the presentation of an art collection in a knowledgeable way. Machine processes are characterized by their capacity to manage and analyze large amounts of data. This paper envisages AI curation and audience interaction to explore the implications of contemporary machine learning models for the curatorial world. This project was developed for the occasion of the 2023 Helsinki Art Biennial, entitled New Directions May Emerge. We use the Helsinki Art Museum (HAM) collection to re-imagine the city of Helsinki through the lens of machine perception. We use visual-textual models to place indoor artworks in public spaces, assigning fictional coordinates based on similarity scores. We transform the space that each artwork inhabits in the city by generating synthetic 360 art panoramas. We guide the generation estimating depth values from 360 panoramas at each artwork location, and machine-generated prompts of the artworks. The result of this project is an AI curation that places the artworks in their imagined physical space, blurring the lines of artwork, context, and machine perception. The work is virtually presented as a web-based installation on this this link, where users can navigate an alternative version of the city while exploring and interacting with its cultural heritage at scale.

Presenter: Ludovica Schaerf

Date: 2023-09-26 15:00 (CEST)