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LP-29: Visual Storytelling and Multifaceted Image Search for Art History
Time:
Friday, 18/July/2025:
2:00pm - 3:30pm
Session Chair: Houda Lamqaddam , Universiteit Van Amsterdam
Location: Aud C1 (EC) Zoom link to be included 142 places
Presentations
Comparing Human and AI Performance in Visual Storytelling through Creation of Comic Strips: A Case Study
Ugur Onal2 , Sanem Sariel2 , Metin Sezgin3 , Ergun Akleman 1
1 TEXAS A&M UNIVERSITY, United States of America; 2 Istanbul Technical University, Istanbul, Turkey; 3 Koc University, Istanbul, Turkey
This study compares humans and AI in recreating a three-panel Nancy cartoon. Humans, with basic art training, excelled in creating coherent visual narratives, while AI, despite impressive artistic replication, struggled with storytelling. The results highlight human superiority in transforming instructions into meaningful stories.
Motif-Match: Redefining Similarity for Digital Art History Through Multifaceted Image Search
Houda Lamqaddam 1 , Ivania Donoso2 , Quinten Mortier2 , Koenraad Brosens2 , Katrien Verbert2
1 Universiteit Van Amsterdam, The Netherlands; 2 KU Leuven, Belgium
This paper introduces a multidimensional similarity search tool, Motif-Match, for digital art history, emphasizing similarity as multi-dimensional, cumulative, and situational. Through participatory design and user evaluation with 39 participants, we explore the roles of control and transparency, offering insights into balancing technical innovation with the nuanced needs of humanities research.