AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2025
AlJadaan, O.; Ibrahim, O.; Ani, N. N. Al; Jabas, A.; Alfaress, M.
Navigating Intellectual Property Rights in the Age of AI and the Metaverse Book Section
In: Studies in Systems, Decision and Control, vol. 234, pp. 219–228, Springer Science and Business Media Deutschland GmbH, 2025, ISBN: 21984182 (ISSN).
Abstract | Links | BibTeX | Tags: AI-generated content, Artificial intelligence, Authorship, Blockchain, Copyright law, Creative industries, Cross-jurisdictional issues, Digital assets, Ethical implications, Intellectual property, IP enforcement, Legal frameworks, Metaverse, Non-fungible tokens (NFTs), Ownership, Patent law, Smart contracts, Virtual goods
@incollection{aljadaan_navigating_2025,
title = {Navigating Intellectual Property Rights in the Age of AI and the Metaverse},
author = {O. AlJadaan and O. Ibrahim and N. N. Al Ani and A. Jabas and M. Alfaress},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003758740&doi=10.1007%2f978-3-031-84636-6_18&partnerID=40&md5=f23526f6ff8a70c783074256ca6351a8},
doi = {10.1007/978-3-031-84636-6_18},
isbn = {21984182 (ISSN)},
year = {2025},
date = {2025-01-01},
booktitle = {Studies in Systems, Decision and Control},
volume = {234},
pages = {219–228},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {The paper examines the challenges that Intellectual Property (IP) rights pose within artificial intelligence (AI) and further into the Metaverse, the constantly developing virtual world wherein one is allowed to create, trade, and own digital assets. The increasing development of AI-generated content and virtual environments has also challenged the traditional notion of authorship and ownership and, thus, to the existing regimes regulating IP. This paper discusses the current legal framework, case studies on AI-generated content, and IP use in Metaverse through smart contracts and blockchain technology. Moreover, this paper examines the ethics involved in such development and public policy reforms that can be implemented in the IP law relating to this evolving technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.},
keywords = {AI-generated content, Artificial intelligence, Authorship, Blockchain, Copyright law, Creative industries, Cross-jurisdictional issues, Digital assets, Ethical implications, Intellectual property, IP enforcement, Legal frameworks, Metaverse, Non-fungible tokens (NFTs), Ownership, Patent law, Smart contracts, Virtual goods},
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tppubtype = {incollection}
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The paper examines the challenges that Intellectual Property (IP) rights pose within artificial intelligence (AI) and further into the Metaverse, the constantly developing virtual world wherein one is allowed to create, trade, and own digital assets. The increasing development of AI-generated content and virtual environments has also challenged the traditional notion of authorship and ownership and, thus, to the existing regimes regulating IP. This paper discusses the current legal framework, case studies on AI-generated content, and IP use in Metaverse through smart contracts and blockchain technology. Moreover, this paper examines the ethics involved in such development and public policy reforms that can be implemented in the IP law relating to this evolving technology. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.
2024
Paweroi, R. M.; Koppen, M.
Framework for Integration of Generative AI into Metaverse Asset Creation Proceedings Article
In: Int. Conf. Intell. Metaverse Technol. Appl., iMETA, pp. 27–33, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835035151-4 (ISBN).
Abstract | Links | BibTeX | Tags: 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
@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}
}
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.
Weng, S. C. -C.; Chiou, Y. -M.; Do, E. Y. -L.
Dream Mesh: A Speech-to-3D Model Generative Pipeline in Mixed Reality Proceedings Article
In: Proc. - IEEE Int. Conf. Artif. Intell. Ext. Virtual Real., AIxVR, pp. 345–349, Institute of Electrical and Electronics Engineers Inc., 2024, ISBN: 979-835037202-1 (ISBN).
Abstract | Links | BibTeX | Tags: 3D content, 3D modeling, 3D models, 3d-modeling, Augmented Reality, Digital assets, Generative AI, generative artificial intelligence, Intelligence models, Mesh generation, Mixed reality, Modeling, Speech-to-3D, Text modeling, Three dimensional computer graphics, User interfaces
@inproceedings{weng_dream_2024,
title = {Dream Mesh: A Speech-to-3D Model Generative Pipeline in Mixed Reality},
author = {S. C. -C. Weng and Y. -M. Chiou and E. Y. -L. Do},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85187218106&doi=10.1109%2fAIxVR59861.2024.00059&partnerID=40&md5=5bfe206e841f23de6458f88a0824bd4d},
doi = {10.1109/AIxVR59861.2024.00059},
isbn = {979-835037202-1 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Proc. - IEEE Int. Conf. Artif. Intell. Ext. Virtual Real., AIxVR},
pages = {345–349},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Generative Artificial Intelligence (AI) models have risen to prominence due to their unparalleled ability to craft and generate digital assets, encompassing text, images, audio, video, and 3D models. Leveraging the capabilities of diffusion models, such as Stable Diffusion and Instruct pix2pix, users can guide AI with specific prompts, streamlining the creative journey for graphic designers. However, the primary application of these models has been to graphic content within desktop interfaces, prompting professionals in interior and architectural design to seek more tailored solutions for their daily operations. To bridge this gap, Augmented Reality (AR) and Mixed Reality (MR) technologies offer a promising solution, transforming traditional 2D artworks into engaging 3D interactive realms. In this paper, we present "Dream Mesh,"a MR application MR tool that combines a Speech-to-3D generative workflow besed on DreamFusion model without relying on pre-existing 3D content libraries. This innovative system empowers users to express 3D content needs through natural language input, promising transformative potential in real-time 3D content creation and an enhanced MR user experience. © 2024 IEEE.},
keywords = {3D content, 3D modeling, 3D models, 3d-modeling, Augmented Reality, Digital assets, Generative AI, generative artificial intelligence, Intelligence models, Mesh generation, Mixed reality, Modeling, Speech-to-3D, Text modeling, Three dimensional computer graphics, User interfaces},
pubstate = {published},
tppubtype = {inproceedings}
}
Generative Artificial Intelligence (AI) models have risen to prominence due to their unparalleled ability to craft and generate digital assets, encompassing text, images, audio, video, and 3D models. Leveraging the capabilities of diffusion models, such as Stable Diffusion and Instruct pix2pix, users can guide AI with specific prompts, streamlining the creative journey for graphic designers. However, the primary application of these models has been to graphic content within desktop interfaces, prompting professionals in interior and architectural design to seek more tailored solutions for their daily operations. To bridge this gap, Augmented Reality (AR) and Mixed Reality (MR) technologies offer a promising solution, transforming traditional 2D artworks into engaging 3D interactive realms. In this paper, we present "Dream Mesh,"a MR application MR tool that combines a Speech-to-3D generative workflow besed on DreamFusion model without relying on pre-existing 3D content libraries. This innovative system empowers users to express 3D content needs through natural language input, promising transformative potential in real-time 3D content creation and an enhanced MR user experience. © 2024 IEEE.