AI-powered Game Recognition: A Collaborative Dataset for Traditional Games

Piette, Eric;Morenville, Achille;Barbara Caré;Dorina Moullou;Piette, Eric
(2025) Computer Applications and Quantitative Methods in Archaeology (CAA) — Location: Athens, Greece (5.May.2025)

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Abstract
We introduce an expert-annotated image dataset of traditional board games and benchmark supervised visual retrieval against the Ludii corpus. Given a photo, our models will rank likely matches with top-k metrics, and we will provide a lightweight web tool for archaeologists to get interpretable suggestions on site. The resource is designed to enable reproducible research and broaden access to cultural-heritage game data.
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Piette, E., Morenville, A., Barbara Caré, Dorina Moullou, & Piette, E. (2025). AI-powered Game Recognition: A Collaborative Dataset for Traditional Games. Computer Applications and Quantitative Methods in Archaeology (CAA), Athens, Greece. https://hdl.handle.net/2078.5/258477