AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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2025
Scofano, L.; Sampieri, A.; Matteis, E. De; Spinelli, I.; Galasso, F.
Social EgoMesh Estimation Proceedings Article
In: Proc. - IEEE Winter Conf. Appl. Comput. Vis., WACV, pp. 5948–5958, Institute of Electrical and Electronics Engineers Inc., 2025, ISBN: 979-833151083-1 (ISBN).
Abstract | Links | BibTeX | Tags: Augmented reality applications, Ego-motion, Egocentric view, Generative AI, Human behaviors, Human mesh recovery, Limited visibility, Recent researches, Three dimensional computer graphics, Video sequences, Virtual and augmented reality
@inproceedings{scofano_social_2025,
title = {Social EgoMesh Estimation},
author = {L. Scofano and A. Sampieri and E. De Matteis and I. Spinelli and F. Galasso},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105003632729&doi=10.1109%2fWACV61041.2025.00580&partnerID=40&md5=3c2b2d069ffb596c64ee8dbc211b74a8},
doi = {10.1109/WACV61041.2025.00580},
isbn = {979-833151083-1 (ISBN)},
year = {2025},
date = {2025-01-01},
booktitle = {Proc. - IEEE Winter Conf. Appl. Comput. Vis., WACV},
pages = {5948–5958},
publisher = {Institute of Electrical and Electronics Engineers Inc.},
abstract = {Accurately estimating the 3D pose of the camera wearer in egocentric video sequences is crucial to modeling human behavior in virtual and augmented reality applications. The task presents unique challenges due to the limited visibility of the user's body caused by the front-facing camera mounted on their head. Recent research has explored the utilization of the scene and ego-motion, but it has overlooked humans' interactive nature. We propose a novel framework for Social Egocentric Estimation of body MEshes (SEE-ME). Our approach is the first to estimate the wearer's mesh using only a latent probabilistic diffusion model, which we condition on the scene and, for the first time, on the social wearer-interactee interactions. Our in-depth study sheds light on when social interaction matters most for ego-mesh estimation; it quantifies the impact of interpersonal distance and gaze direction. Overall, SEEME surpasses the current best technique, reducing the pose estimation error (MPJPE) by 53%. The code is available at SEEME. © 2025 IEEE.},
keywords = {Augmented reality applications, Ego-motion, Egocentric view, Generative AI, Human behaviors, Human mesh recovery, Limited visibility, Recent researches, Three dimensional computer graphics, Video sequences, Virtual and augmented reality},
pubstate = {published},
tppubtype = {inproceedings}
}
2024
Do, M. D.; Dahlem, N.; Paulus, M.; Krick, M.; Steffny, L.; Werth, D.
“Furnish Your Reality” - Intelligent Mobile AR Application for Personalized Furniture Proceedings Article
In: J., Wei; G., Margetis (Ed.): Lect. Notes Comput. Sci., pp. 196–210, Springer Science and Business Media Deutschland GmbH, 2024, ISBN: 03029743 (ISSN); 978-303160457-7 (ISBN).
Abstract | Links | BibTeX | Tags: Artificial intelligence, Augmented Reality, Augmented reality applications, Electronic commerce, Generative AI, generative artificial intelligence, Human computer interaction, Human computer interfaces, LiDAR, Mobile augmented reality, Mobile human computer interface, Mobile Human Computer Interfaces, Personalized product design, Personalized products, Phygital customer journey, Physical environments, Product design, Recommender system, Recommender systems, Sales, User centered design, User interfaces, User-centered design
@inproceedings{do_furnish_2024,
title = {“Furnish Your Reality” - Intelligent Mobile AR Application for Personalized Furniture},
author = {M. D. Do and N. Dahlem and M. Paulus and M. Krick and L. Steffny and D. Werth},
editor = {Wei J. and Margetis G.},
url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85196202642&doi=10.1007%2f978-3-031-60458-4_14&partnerID=40&md5=017510be06c286789867235cfd98bb36},
doi = {10.1007/978-3-031-60458-4_14},
isbn = {03029743 (ISSN); 978-303160457-7 (ISBN)},
year = {2024},
date = {2024-01-01},
booktitle = {Lect. Notes Comput. Sci.},
volume = {14737 LNCS},
pages = {196–210},
publisher = {Springer Science and Business Media Deutschland GmbH},
abstract = {Today’s online retailers are faced with the challenge of providing a convenient solution for their customers to browse through a wide range of products. Simultaneously, they must meet individual customer needs by creating unique, personalized, one-of-a-kind items. Technological advances in areas such as Augmented Reality (AR), Artificial Intelligence (AI) or sensors (e.g. LiDAR), have the potential to address these challenges by enhancing the customer experience in new ways. One option is to implement “phygital” commerce solutions, which combines the benefits of physical and digital environments to improve the customer journey. This work presents a concept for a mobile AR application that integrates LiDAR and an AI-powered recommender system to create a unique phygital customer journey in the context of furniture shopping. The combination of AR, LiDAR and AI enables an accurate immersive experience along with personalized product designs. This concept aims to deliver benefits in terms of usability, convenience, time savings and user experience, while bridging the gap between mass-produced and personalized products. The new possibilities for merging virtual with physical environments hold immense potential, but this work also highlights challenges for customers as well as for online platform providers and future researchers. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.},
keywords = {Artificial intelligence, Augmented Reality, Augmented reality applications, Electronic commerce, Generative AI, generative artificial intelligence, Human computer interaction, Human computer interfaces, LiDAR, Mobile augmented reality, Mobile human computer interface, Mobile Human Computer Interfaces, Personalized product design, Personalized products, Phygital customer journey, Physical environments, Product design, Recommender system, Recommender systems, Sales, User centered design, User interfaces, User-centered design},
pubstate = {published},
tppubtype = {inproceedings}
}