| license: mit | |
| task_categories: | |
| - text-to-3d | |
| - image-to-3d | |
| # Garment Particles: A 2D–3D Symmetric Garment Representation for Generation and Editing | |
| [Project Page](https://garment-particles.github.io) | [Paper](https://huggingface.co/papers/2605.26391) | [GitHub](https://github.com/garment-particles/GarmentParticles) | |
| Garment Particles is a 5D point-cloud representation that jointly encodes 2D sewing patterns and 3D geometry. This representation enables Garment Particles Flow (GPF), a framework that supports intuitive garment generation from high-level inputs such as text, images, and sketches, as well as various editing operations. | |
| ## Dataset Structure | |
| The dataset consists of: | |
| - `data/particles-*.tar`: 26 shards of per-garment particle data (`rand_<id>/garment_particles_rand_<id>.h5` + `stats.txt`). | |
| - `splits/garment_particle_v2_{train,test}_11182025.txt`: Train and test split files. | |
| ## Usage | |
| As described in the [official repository](https://github.com/garment-particles/GarmentParticles), you can download and unpack the shards using the Hugging Face CLI: | |
| ```bash | |
| # Download the shards | |
| huggingface-cli download georgeNakayama/GarmentParticles --repo-type dataset --local-dir garment_data | |
| # Unpack the shards | |
| cd garment_data | |
| for t in data/*.tar; do tar -xf "$t"; done | |
| cd .. | |
| ``` | |
| This will extract the data into a structure like `garment_data/rand_<id>/garment_particles_rand_<id>.h5`. | |
| ## Citation | |
| ```bibtex | |
| @article{garmentparticles2026, | |
| title={Garment Particles: A 2D--3D Symmetric Garment Representation for Generation and Editing}, | |
| author={Nakayama, George and others}, | |
| journal={SIGGRAPH Conference Papers}, | |
| year={2026} | |
| } | |
| ``` |