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GarmentCodeData: A Dataset of 3D Made-to-Measure Garments with Sewing Patterns

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Computer Vision – ECCV 2024 (ECCV 2024)

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Abstract

Recent research interest in learning-based processing of garments, from virtual fitting to generation and reconstruction, stumbles on a scarcity of high-quality public data in the domain. We contribute to resolving this need by presenting the first large-scale synthetic dataset of 3D made-to-measure garments with sewing patterns, as well as its generation pipeline. GarmentCodeData contains 115,000 data points that cover a variety of designs in many common garment categories: tops, shirts, dresses, jumpsuits, skirts, pants, etc., fitted to a variety of body shapes sampled from a custom statistical body model based on CAESAR [28], as well as a standard reference body shape, applying three different textile materials. To enable the creation of datasets of such complexity, we introduce a set of algorithms for automatically taking tailor’s measures on sampled body shapes, sampling strategies for sewing pattern design, and propose an automatic, open-source 3D garment draping pipeline based on a fast XPBD simulator [22], while contributing several solutions for collision resolution and drape correctness to enable scalability.

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Notes

  1. 1.

    https://igl.ethz.ch/projects/GarmentCodeData/.

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Acknowledgments

This work was supported by the European Research Council (ERC) under the European Union’s Horizon 2020 Research and Innovation Programme (ERC Consolidator Grant, agreement No. 101003104, MYCLOTH). Stephan Wenninger has been funded by “Stiftung Innovation in der Hochschullehre” through the project “Hybrid Learning Center” (FBM2020-EA-690-01130). We thank Ami Beuret for his help in refactoring GarmentCode codebase. We are grateful to Jana Schuricht for her professional consultations on patternmaking and to members of IGL and GGG for their continuous support and cheer throughout this project.

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Authors and Affiliations

  1. ETH Zurich, Rämistrasse 101, 8092, Zurich, Switzerland

    Maria Korosteleva, Timur Levent Kesdogan, Jasmin Koller, Yuhan Zhang & Olga Sorkine-Hornung

  2. TU Dortmund University, Otto-Hahn-Strasse 16, 44227, Dortmund, Germany

    Fabian Kemper, Stephan Wenninger & Mario Botsch

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  1. Maria Korosteleva
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Correspondence to Maria Korosteleva .

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Editors and Affiliations

  1. University of Birmingham, Birmingham, UK

    Aleš Leonardis

  2. University of Trento, Trento, Italy

    Elisa Ricci

  3. Technical University of Darmstadt, Darmstadt, Germany

    Stefan Roth

  4. Princeton University, Princeton, NJ, USA

    Olga Russakovsky

  5. Czech Technical University in Prague, Prague, Czech Republic

    Torsten Sattler

  6. École des Ponts ParisTech, Marne-la-Vallée, France

    Gül Varol

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Korosteleva, M. et al. (2025). GarmentCodeData: A Dataset of 3D Made-to-Measure Garments with Sewing Patterns. In: Leonardis, A., Ricci, E., Roth, S., Russakovsky, O., Sattler, T., Varol, G. (eds) Computer Vision – ECCV 2024. ECCV 2024. Lecture Notes in Computer Science, vol 15118. Springer, Cham. https://doi.org/10.1007/978-3-031-73027-6_7

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