Publications

@inproceedings{sahebnasi_exploring_2024,

title = {Exploring the Potential of Generative AI in Prototyping XR Applications},

author = {M. J. Sahebnasi and M. Farrokhimaleki and N. Wang and R. Zhao and F. Maurer},

editor = {Wang N. and Bellucci A. and Anthes C. and Daeijavad P. and Friedl-Knirsch J. and Maurer F. and Pointecker F. and Spano L.D.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196093148&partnerID=40&md5=a6264c6add18b5cd0ff99a0d3b25b822},

isbn = {16130073 (ISSN)},

year  = {2024},

date = {2024-01-01},

booktitle = {CEUR Workshop Proc.},

volume = {3704},

publisher = {CEUR-WS},

abstract = {This paper presents the initial stage of our research to develop a novel approach to streamline the prototyping of Extended Reality applications using generative AI models. We introduce a tool that leverages state-of-the-art generative AI techniques to facilitate the prototyping process, including 3D asset generation and scene composition. The tool allows users to verbally articulate their prototypes, which are then generated by an AI model. We aim to make the development of XR applications more efficient by empowering the designers to gather early feedback from users through rapidly developed prototypes. © 2024 Copyright for this paper by its authors.},

keywords = {AI techniques, Extended reality, generative artificial intelligence, Prototyping, Prototyping process, Scene composition, Software prototyping, State of the art},

pubstate = {published},

tppubtype = {inproceedings}

}