Tangible Diffusion: Exploring Artwork Generation via Tangible Elements and Artificial Intelligence in Arts and Design Education

Abstract
Generative models have revolutionized the field of art and design, providing an emerging and accessible approach to creating diverse artwork. However, effectively utilizing these models still requires significant expertise, making the system inaccessible to novice users, such as young children. This paper introduces a novel approach to artwork generation, combining tangible elements with AI generative models, resulting in a more engaging and immersive learning experience. With materials prepared by teachers, students can easily create digital artwork by manipulating tangible building blocks. The experiments demonstrate that the proposed pipeline can be applied to various scenarios, using either off-the-shelf or carefully designed tangible elements. This approach provides an interdisciplinary learning platform for arts and design education, fostering creativity and exploration of various art styles and design topics.
Authors
Kuntong Han, Keyang Tang, Meng Wang
Publication Year
2024
https://dl.acm.org/doi/abs/10.1145/3623509.3633394
Publication Venue
The ACM International Conference on Tangible, Embedded and Embodied Interaction (TEI)
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