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
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}
}
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.
2023
Stacchio, L.; Scorolli, C.; Marfia, G.
Evaluating Human Aesthetic and Emotional Aspects of 3D generated content through eXtended Reality Proceedings Article
In: A., De Filippo; M., Milano; V., Presutti; A., Saffiotti (Ed.): CEUR Workshop Proc., pp. 38–49, CEUR-WS, 2023, ISBN: 16130073 (ISSN).
Abstract | Links | BibTeX | Tags: aesthetic evaluation, Creative industries, Deep learning, Effective tool, Emotional aspect, Entertainment industry, Esthetic evaluation, Extended reality, generative artificial intelligence, Human-in-the-loop, Learning systems, Metaverses, Multimedia contents, Production efficiency, Three dimensional computer graphics, Virtual Reality
@inproceedings{stacchio_evaluating_2023,
title = {Evaluating Human Aesthetic and Emotional Aspects of 3D generated content through eXtended Reality},
author = {L. Stacchio and C. Scorolli and G. Marfia},
editor = {De Filippo A. and Milano M. and Presutti V. and Saffiotti A.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176617276&partnerID=40&md5=14d9d23320d6ed236cbb4b0c562bec06},
isbn = {16130073 (ISSN)},
year = {2023},
date = {2023-01-01},
booktitle = {CEUR Workshop Proc.},
volume = {3519},
pages = {38–49},
publisher = {CEUR-WS},
abstract = {The Metaverse era is rapidly shaping novel and effective tools particularly useful in the entertainment and creative industry. A fundamental role is played by modern generative deep learning models, that can be used to provide varied and high-quality multimedia content, considerably lowering costs while increasing production efficiency. The goodness of such models is usually evaluated quantitatively with established metrics on data and humans using simple constructs such as the Mean Opinion Score. However, these scales and scores don't take into account the aesthetical and emotional components, which could play a role in positively controlling the automatic generation of multimedia content while at the same time introducing novel forms of human-in-the-loop in generative deep learning. Furthermore, considering data such as 3D models/scenes, and 360° panorama images and videos, conventional display hardware may not be the most effective means for human evaluation. A first solution to such a problem could consist of employing eXtendend Reality paradigms and devices. Considering all such aspects, we here discuss a recent contribution that adopted a well-known scale to evaluate the aesthetic and emotional experience of watching a 360° video of a musical concert in Virtual Reality (VR) compared to a classical 2D webstream, showing that adopting fully immersive VR experience could be a possible path to follow. © 2023 CEUR-WS. All rights reserved.},
keywords = {aesthetic evaluation, Creative industries, Deep learning, Effective tool, Emotional aspect, Entertainment industry, Esthetic evaluation, Extended reality, generative artificial intelligence, Human-in-the-loop, Learning systems, Metaverses, Multimedia contents, Production efficiency, Three dimensional computer graphics, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
The Metaverse era is rapidly shaping novel and effective tools particularly useful in the entertainment and creative industry. A fundamental role is played by modern generative deep learning models, that can be used to provide varied and high-quality multimedia content, considerably lowering costs while increasing production efficiency. The goodness of such models is usually evaluated quantitatively with established metrics on data and humans using simple constructs such as the Mean Opinion Score. However, these scales and scores don't take into account the aesthetical and emotional components, which could play a role in positively controlling the automatic generation of multimedia content while at the same time introducing novel forms of human-in-the-loop in generative deep learning. Furthermore, considering data such as 3D models/scenes, and 360° panorama images and videos, conventional display hardware may not be the most effective means for human evaluation. A first solution to such a problem could consist of employing eXtendend Reality paradigms and devices. Considering all such aspects, we here discuss a recent contribution that adopted a well-known scale to evaluate the aesthetic and emotional experience of watching a 360° video of a musical concert in Virtual Reality (VR) compared to a classical 2D webstream, showing that adopting fully immersive VR experience could be a possible path to follow. © 2023 CEUR-WS. All rights reserved.