- publication
- European Conference on Computer Vision (ECCV) 2024
- authors
- Maria Korosteleva, Timur Levent Kesdogan, Fabian Kemper, Stephan Wenninger, Jasmin Koller, Yuhan Zhang, Mario Botsch, Olga Sorkine-Hornung
Samples from GarmentCodeData showcasing the breadth of represented garment styles and body shapes.
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, 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, while contributing several solutions for collision resolution and drape correctness to enable scalability.
[Sept 4th, 2024] GarmentCodeData version update. See more details in documentation for v2.
downloads
- Paper
- GarmentCodeData dataset (v2)
- BibTex entry
- Code on GitHub
- Demo garment configurator
- Presentation video
video
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-EA690-01130). 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 the members of IGL and GGG for their continuous support and cheer throughout this project.