VolHuMe: a High-Resolution Large Scale Dataset of Volumetric Human Meshes

Giulia Martinelli; Niccolò Bisagno; Nicola Garau; Esa Rahtu; Nicola Conci

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arXiv · 2606.23062

VolHuMe: a High-Resolution Large Scale Dataset of Volumetric Human Meshes

Giulia Martinelli·Niccolò Bisagno·Nicola Garau·Esa Rahtu·Nicola Conci

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Abstract

We introduce VolHuMe, a dataset of high-quality 4D human scans captured with a state-of-the-art volumetric studio using 64 RGB and 32 depth cameras. VolHuMe contains individual captures of 104 subjects and provides extensive ground truth, including SMPL-X, high-resolution meshes, multi-view RGB/depth images, rigged meshes, point clouds, garment segmentation, and detailed hand and facial geometry. Unlike prior datasets that primarily rely on full-body imagery, VolHuMe uses a close-range, high-resolution capture setup that preserves fine-grained body-part details, improving geometric fidelity and texture resolution. We benchmark VolHuMe on state-of-the-art methods across 3D and 4D human reconstruction tasks, showcasing the dataset's quality and exposing the limitations of current evaluation testbeds.

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Giulia Martinelli, Niccolò Bisagno, Nicola Garau, Esa Rahtu, Nicola Conci. 2026-06-22. VolHuMe: a High-Resolution Large Scale Dataset of Volumetric Human Meshes. https://arxiv.org/abs/2606.23062

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