Abstract
Today, an increasing number of applications in domains such as cultural heritage, healthcare, education, entertainment, and fashion require high-fidelity 3D avatars. However, generating avatars that faithfully reproduce users’ bodies through modeling or acquisition techniques remains challenging and time-consuming, particularly in applications where the accurate quantitative reproduction of body shape and precise anthropometric measurements is required. Thus, attention is shifting towards machine learning-based approaches, in particular those able to fit a parametric model representing the avatar to the intended body shape. Among these models, the Sparse Unified Part-Based Human Representation (SUPR) has been proven to offer superior performance compared to other representations. However, its adoption is primarily hindered by the lack of datasets built upon it. This paper addresses this gap by proposing BOdy shape parameter and 3D meshes of Individuals basEd on SUPR (BODIES), a dataset containing 84,000 synthetic-generated subjects described using the SUPR model with different numbers of parameters. The paper also presents the results of three experimental studies aimed at assessing the improvements brought by the SUPR model over the state-of-the-art when used to feed an existing framework for generating 3D avatar meshes.
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Data availability
The BODIES dataset is available for download at28.
Code availability
The source code that can be used to run the experiments described in this paper is available at https://tinyurl.com/kmrk4rwj.
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Acknowledgements
This research was developed in collaboration with Protocube Reply and was supported by PON “Ricerca e Innovazione” 2014-2020 - DM 1062/2021 funds. The authors want to thank Kundan Sai Prabhu Thota, one of the authors of2, for his support through the configuration and usage of the framework that was then optimized and used for the experimental studies.
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Federica Moro and Francesco Manigrasso contributed to the design and development of the dataset, as well as the implementation of the experimental studies. Alberto Cannavò contributed to the design of the experimental studies and to the initial drafting of the paper. Fabrizio Lamberti contributed to the design of the experimental studies, as well as to the writing and revision of the paper.
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Cannavò, A., Manigrasso, F., Moro, F. et al. BODIES: BOdy shape parameter and 3D meshes of Individuals basEd on SUPR. Sci Data (2026). https://doi.org/10.1038/s41597-026-06777-4
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DOI: https://doi.org/10.1038/s41597-026-06777-4
