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.
2024
Rausa, M.; Gaglio, S.; Augello, A.; Caggianese, G.; Franchini, S.; Gallo, L.; Sabatucci, L.
Enriching Metaverse with Memories Through Generative AI: A Case Study Proceedings Article
In: IEEE Int. Conf. Metrol. Ext. Real., Artif. Intell. Neural Eng., MetroXRAINE - Proc., pp. 371–376, Institute of Electrical and Electronics Engineers Inc., St Albans, United Kingdom, 2024, ISBN: 979-835037800-9 (ISBN).
Abstract | Links | BibTeX | Tags: 3D modeling, 3D models, 3D reconstruction, 3d-modeling, Case-studies, Generative adversarial networks, Generative AI, Input modes, Metamemory, Metaverses, Synthetic Data Generation, Synthetic data generations, Textual description, Virtual environments, Virtual Reality
@inproceedings{rausa_enriching_2024,
title = {Enriching Metaverse with Memories Through Generative AI: A Case Study},
author = {M. Rausa and S. Gaglio and A. Augello and G. Caggianese and S. Franchini and L. Gallo and L. Sabatucci},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85216124702&doi=10.1109%2fMetroXRAINE62247.2024.10796338&partnerID=40&md5=580d0727ab8740a6ada62eeef5ac283f},
doi = {10.1109/MetroXRAINE62247.2024.10796338},
isbn = {979-835037800-9 (ISBN)},
year = {2024},
date = {2024-01-01},
urldate = {2025-01-07},
booktitle = {IEEE Int. Conf. Metrol. Ext. Real., Artif. Intell. Neural Eng., MetroXRAINE - Proc.},
pages = {371–376},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
address = {St Albans, United Kingdom},
abstract = {The paper introduces MetaMemory, an approach to generate 3D models from either textual descriptions or photographs of objects, offering dual input modes for enhanced representation. MetaMemory's architecture is discussed presenting the tools employed in extracting the object from the image, generating the 3D mesh from texts or images, and visualizing the object reconstruction in an immersive scenario. Afterwards, a case study in which we experienced reconstructing memories of ancient crafts is examined together with the achieved results, by highlighting current limitations and potential applications. © 2024 IEEE.},
keywords = {3D modeling, 3D models, 3D reconstruction, 3d-modeling, Case-studies, Generative adversarial networks, Generative AI, Input modes, Metamemory, Metaverses, Synthetic Data Generation, Synthetic data generations, Textual description, Virtual environments, Virtual Reality},
pubstate = {published},
tppubtype = {inproceedings}
}
The paper introduces MetaMemory, an approach to generate 3D models from either textual descriptions or photographs of objects, offering dual input modes for enhanced representation. MetaMemory's architecture is discussed presenting the tools employed in extracting the object from the image, generating the 3D mesh from texts or images, and visualizing the object reconstruction in an immersive scenario. Afterwards, a case study in which we experienced reconstructing memories of ancient crafts is examined together with the achieved results, by highlighting current limitations and potential applications. © 2024 IEEE.