AHCI RESEARCH GROUP

Publications

Papers published in international journals,
proceedings of conferences, workshops and books.

OUR RESEARCH

Scientific Publications

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2025

Stacchio, L.; Balloni, E.; Frontoni, E.; Paolanti, M.; Zingaretti, P.; Pierdicca, R.

MineVRA: Exploring the Role of Generative AI-Driven Content Development in XR Environments through a Context-Aware Approach Journal Article

In: IEEE Transactions on Visualization and Computer Graphics, vol. 31, no. 5, pp. 3602–3612, 2025, ISSN: 10772626 (ISSN).

Abstract | Links | BibTeX | Tags: adult, Article, Artificial intelligence, Computer graphics, Computer vision, Content Development, Contents development, Context-Aware, Context-aware approaches, Extended reality, female, Generative adversarial networks, Generative AI, generative artificial intelligence, human, Human-in-the-loop, Immersive, Immersive environment, male, Multi-modal, User need, Virtual environments, Virtual Reality

@article{stacchio_minevra_2025,

title = {MineVRA: Exploring the Role of Generative AI-Driven Content Development in XR Environments through a Context-Aware Approach},

author = {L. Stacchio and E. Balloni and E. Frontoni and M. Paolanti and P. Zingaretti and R. Pierdicca},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003746367&doi=10.1109%2fTVCG.2025.3549160&partnerID=40&md5=70b162b574eebbb0cb71db871aa787e1},

doi = {10.1109/TVCG.2025.3549160},

issn = {10772626 (ISSN)},

year  = {2025},

date = {2025-01-01},

journal = {IEEE Transactions on Visualization and Computer Graphics},

volume = {31},

number = {5},

pages = {3602–3612},

abstract = {The convergence of Artificial Intelligence (AI), Computer Vision (CV), Computer Graphics (CG), and Extended Reality (XR) is driving innovation in immersive environments. A key challenge in these environments is the creation of personalized 3D assets, traditionally achieved through manual modeling, a time-consuming process that often fails to meet individual user needs. More recently, Generative AI (GenAI) has emerged as a promising solution for automated, context-aware content generation. In this paper, we present MineVRA (Multimodal generative artificial iNtelligence for contExt-aware Virtual Reality Assets), a novel Human-In-The-Loop (HITL) XR framework that integrates GenAI to facilitate coherent and adaptive 3D content generation in immersive scenarios. To evaluate the effectiveness of this approach, we conducted a comparative user study analyzing the performance and user satisfaction of GenAI-generated 3D objects compared to those generated by Sketchfab in different immersive contexts. The results suggest that GenAI can significantly complement traditional 3D asset libraries, with valuable design implications for the development of human-centered XR environments. © 1995-2012 IEEE.},

keywords = {adult, Article, Artificial intelligence, Computer graphics, Computer vision, Content Development, Contents development, Context-Aware, Context-aware approaches, Extended reality, female, Generative adversarial networks, Generative AI, generative artificial intelligence, human, Human-in-the-loop, Immersive, Immersive environment, male, Multi-modal, User need, Virtual environments, Virtual Reality},

pubstate = {published},

tppubtype = {article}

}

2023

Yeo, J. Q.; Wang, Y.; Tanary, S.; Cheng, J.; Lau, M.; Ng, A. B.; Guan, F.

AICRID: AI-Empowered CR For Interior Design Proceedings Article

In: G., Bruder; A.H., Olivier; A., Cunningham; E.Y., Peng; J., Grubert; I., Williams (Ed.): Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct, pp. 837–841, Institute of Electrical and Electronics Engineers Inc., 2023, ISBN: 979-835032891-2 (ISBN).

Abstract | Links | BibTeX | Tags: 3D modeling, 3D models, 3d-modeling, Architectural design, Artificial intelligence, Artificial intelligence technologies, Augmented Reality, Augmented reality technology, Interior Design, Interior designs, machine learning, Machine-learning, Model generation, Novel design, Text images, User need, Visualization

@inproceedings{yeo_aicrid_2023,

title = {AICRID: AI-Empowered CR For Interior Design},

author = {J. Q. Yeo and Y. Wang and S. Tanary and J. Cheng and M. Lau and A. B. Ng and F. Guan},

editor = {Bruder G. and Olivier A.H. and Cunningham A. and Peng E.Y. and Grubert J. and Williams I.},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85180375829&doi=10.1109%2fISMAR-Adjunct60411.2023.00184&partnerID=40&md5=b14d89dbd38a4dfe3f85b90800d42e78},

doi = {10.1109/ISMAR-Adjunct60411.2023.00184},

isbn = {979-835032891-2 (ISBN)},

year  = {2023},

date = {2023-01-01},

booktitle = {Proc. - IEEE Int. Symp. Mixed Augment. Real. Adjunct, ISMAR-Adjunct},

pages = {837–841},

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

abstract = {Augmented Reality (AR) technologies have been utilized for interior design for years. Normally 3D furniture models need to be created manually or by scanning with specialized devices and this is usually a costly process. Additionally, users need controllers or hands for manipulating the virtual furniture which may lead to fatigue for long-time usage. Artificial Intelligence (AI) technologies have made it possible to generate 3D models from texts, images or both and show potential to automate interactions through the user's voice. We propose a novel design, AICRID in short, which aims to automate the 3D model generation and to facilitate the interactions for interior design AR by leveraging on AI technologies. Specifically, our design will allow the users to directly generate 3D furniture models with generative AI, enabling them to directly interact with the virtual objects through their voices. © 2023 IEEE.},

keywords = {3D modeling, 3D models, 3d-modeling, Architectural design, Artificial intelligence, Artificial intelligence technologies, Augmented Reality, Augmented reality technology, Interior Design, Interior designs, machine learning, Machine-learning, Model generation, Novel design, Text images, User need, Visualization},

pubstate = {published},

tppubtype = {inproceedings}

}