georgeNakayama/GarmentParticles

Garment Particles: A 2D–3D Symmetric Garment Representation for Generation and Editing

Project Page | Paper | GitHub

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, you can download and unpack the shards using the Hugging Face CLI:

# 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

@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}
}