Publications

@inproceedings{paweroi_framework_2024,

title = {Framework for Integration of Generative AI into Metaverse Asset Creation},

author = {R. M. Paweroi and M. Koppen},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216024340&doi=10.1109%2fiMETA62882.2024.10808057&partnerID=40&md5=00373291c3d224b53759dc39ed9fd65c},

doi = {10.1109/iMETA62882.2024.10808057},

isbn = {979-835035151-4 (ISBN)},

year  = {2024},

date = {2024-01-01},

booktitle = {Int. Conf. Intell. Metaverse Technol. Appl., iMETA},

pages = {27–33},

publisher = {Institute of Electrical and Electronics Engineers Inc.},

abstract = {Metaverse, a virtual world, is developing rapidly and is widely used in multi-sector. The number of users is projected to increase year over year. Due to the development of the metaverse platform, digital asset creation is demanding. Creating high-quality and diverse 3D digital objects is challenging. This study proposes the frameworks for integrating generative AI to create diverse 3D assets into the metaverse. We study different approaches for asset creation, i.e., generative 3D model-based, generative image projection-based, and generative language script-based. Creators can use this workflow to optimize the creation of 3D assets. Moreover, this study compares the results of generative AI and procedural generation on generating diverse 3D objects. The result shows that generative AI can simplify 3D creation and generate more diverse objects. © 2024 IEEE.},

keywords = {3D Asset Creation, 3D Asset Diversity, 3D models, 3d-modeling, Digital assets, Digital Objects, Generative adversarial networks, Generative AI, High quality, Metaverse, Metaverses, Virtual worlds},

pubstate = {published},

tppubtype = {inproceedings}

}