TY - GEN
T1 - Spot The Difference
T2 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems, CHI EA 2023
AU - Hong, Yeong Gi
AU - Jeong, Jae Yeop
AU - Jeong, Jin Woo
AU - Lukianova, Elizaveta
N1 - Publisher Copyright:
© 2023 Owner/Author.
PY - 2023/4/19
Y1 - 2023/4/19
N2 - Play and games are an inseparable part of our lives, and we have been playing various games from our childhood to adulthood. One of the widely recognized games is "Spot-the-Difference", which has been played and employed in a variety of domains, such as education, training, and entertainment. However, designing a custom "Spot-the-Difference"game for a certain domain requires consideration in terms of the level of game difficulty, game interest, and human intervention, therefore, is non-trivial. In this paper, we propose a novel framework based on Human-AI collaboration to automatically generate images for the "Spot-the-Difference"game. We employ Maskformer and Inpainting Stable Diffusion to automatically identify and re-draw a set of regions in the image. Finally, we conducted a user study with 19 participants to evaluate our framework. From the experimental result, we found that AI-generated game images were enjoyable, but there is still room for improvement in the quality of the overall game playing.
AB - Play and games are an inseparable part of our lives, and we have been playing various games from our childhood to adulthood. One of the widely recognized games is "Spot-the-Difference", which has been played and employed in a variety of domains, such as education, training, and entertainment. However, designing a custom "Spot-the-Difference"game for a certain domain requires consideration in terms of the level of game difficulty, game interest, and human intervention, therefore, is non-trivial. In this paper, we propose a novel framework based on Human-AI collaboration to automatically generate images for the "Spot-the-Difference"game. We employ Maskformer and Inpainting Stable Diffusion to automatically identify and re-draw a set of regions in the image. Finally, we conducted a user study with 19 participants to evaluate our framework. From the experimental result, we found that AI-generated game images were enjoyable, but there is still room for improvement in the quality of the overall game playing.
KW - Game
KW - Generative AI
KW - Image Generation
KW - Instance Segmentation
UR - http://www.scopus.com/inward/record.url?scp=85158121199&partnerID=8YFLogxK
U2 - 10.1145/3544549.3585879
DO - 10.1145/3544549.3585879
M3 - Conference contribution
AN - SCOPUS:85158121199
T3 - Conference on Human Factors in Computing Systems - Proceedings
BT - CHI 2023 - Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems
PB - Association for Computing Machinery
Y2 - 23 April 2023 through 28 April 2023
ER -