Papers › Art2Mus: Bridging Visual Arts and Music through Cross-Modal Generation
Art2Mus: Bridging Visual Arts and Music through Cross-Modal Generation
Ivan Rinaldi, Nicola Fanelli, Giovanna Castellano, Gennaro Vessio
Artificial Intelligence and generative models have revolutionized music creation, with many models leveraging textual or visual prompts for guidance. However, existing image-to-music models are limited to simple images, lacking the capability to generate music from complex digitized artworks. To address this gap, we introduce 𝒜rt2ℳus, a novel model designed to create music from digitized artworks or text inputs. 𝒜rt2ℳus extends the AudioLDM~2 architecture, a text-to-audio model, and employs our newly curated datasets, created via ImageBind, which pair digitized artworks with music. Experimental results demonstrate that 𝒜rt2ℳus can generate music that resonates with the input stimuli. These findings suggest promising applications in multimedia art, interactive installations, and AI-driven creative tools.
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