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

arXiv: https://arxiv.org/abs/2605.26391 · HTML: https://mlsanity.com/paper/2605.26391/

## Key facts

- Cited by 2 papers in the map (data through 14 Oct 2026).
- Builds on 22 of its 72 references that are in the map.
- First posted on arXiv 25 May 2026.

## Builds on (most cited first, 22 of 22)

- [Diffusion Posterior Sampling for General Noisy Inverse Problems](https://mlsanity.com/paper/2209.14687/) (2022)
- [CLAY: A Controllable Large-scale Generative Model for Creating High-quality 3D Assets](https://mlsanity.com/paper/2406.13897/) (2024)
- [Trace and Pace: Controllable Pedestrian Animation via Guided Trajectory Diffusion](https://mlsanity.com/paper/2304.01893/) (2023)
- [BrepGen: A B-rep Generative Diffusion Model with Structured Latent Geometry](https://mlsanity.com/paper/2401.15563/) (2024)
- [FlowDPS: Flow-Driven Posterior Sampling for Inverse Problems](https://mlsanity.com/paper/2503.08136/) (2025)
- [FasterDiT: Towards Faster Diffusion Transformers Training without Architecture Modification](https://mlsanity.com/paper/2410.10356/) (2024)
- [Fashionpedia: Ontology, Segmentation, and an Attribute Localization Dataset](https://mlsanity.com/paper/2004.12276/) (2020)
- [Learning a Shared Shape Space for Multimodal Garment Design](https://mlsanity.com/paper/1806.11335/) (2018)
- [ISP: Multi-Layered Garment Draping with Implicit Sewing Patterns](https://mlsanity.com/paper/2305.14100/) (2023)
- [HoLa: B-Rep Generation using a Holistic Latent Representation](https://mlsanity.com/paper/2504.14257/) (2025)
- [GarmentCodeData: A Dataset of 3D Made-to-Measure Garments With Sewing Patterns](https://mlsanity.com/paper/2405.17609/) (2024)
- [GarmentCode: Programming Parametric Sewing Patterns](https://mlsanity.com/paper/2306.03642/) (2023)
- [Computational Pattern Making from 3D Garment Models](https://mlsanity.com/paper/2202.10272/) (2022)
- [Dress-1-to-3: Single Image to Simulation-Ready 3D Outfit with Diffusion Prior and Differentiable Physics](https://mlsanity.com/paper/2502.03449/) (2025)
- [Single View Garment Reconstruction Using Diffusion Mapping Via Pattern Coordinates](https://mlsanity.com/paper/2504.08353/) (2025)
- [GarmentImage: Raster Encoding of Garment Sewing Patterns with Diverse Topologies](https://mlsanity.com/paper/2505.02592/) (2025)
- [NeuralTailor: Reconstructing Sewing Pattern Structures from 3D Point Clouds of Garments](https://mlsanity.com/paper/2201.13063/) (2022)
- [GarmentDiffusion: 3D Garment Sewing Pattern Generation with Multimodal Diffusion Transformers](https://mlsanity.com/paper/2504.21476/) (2025)
- [Designing Personalized Garments with Body Movement](https://mlsanity.com/paper/2102.05462/) (2021)
- [SPGen: Spherical Projection as Consistent and Flexible Representation for Single Image 3D Shape Generation](https://mlsanity.com/paper/2509.12721/) (2025)
- [GarmageNet: A Multimodal Generative Framework for Sewing Pattern Design and Generic Garment Modeling](https://mlsanity.com/paper/2504.01483/) (2025)
- [Dress Anyone : Automatic Physically-Based Garment Pattern Refitting](https://mlsanity.com/paper/2405.19148/) (2024)

## Built on by (most cited first, 2 of 2)

- [Stitched Embeddings: A Unified Latent Space for 3D Garments and 2D Patterns](https://mlsanity.com/paper/2607.00829/) (2026)
- [SewFusion: Tailored Generation of Topology and Panel-Level Geometry for Sewing Patterns](https://mlsanity.com/paper/2609.23548/) (2026)

## Abstract (arXiv)

Practical garment design spans two modes: intuitive creation from high-level intent, such as a reference image or text description, and complex low-level editing across 2D sewing patterns and 3D draped geometry, which requires professional training to navigate their complex interdependencies. Yet existing frameworks address only part of this challenge, offering either garment generation from casual inputs or direct editing on sewing patterns. To support both ends of the spectrum, we propose Garment Particles, a 5D point-cloud representation that jointly encodes 2D sewing patterns and 3D geometry. This representation enables Garment Particles Flow (GPF), a rectified flow framework that supports intuitive generation from high-level inputs (text, images, sketches) and various editing operations on 2D sewing patterns and 3D geometries via diffusion posterior sampling. Finally, we introduce Particles-to-Pattern Flow that converts generated garment particles into curved-based patterns for simulation. We validate our model's generation ability on multiple datasets, achieving state-of-the-art garment generation results against competitive baselines. Our model also enables many garment editing scenarios, including garment interpolation, sewing pattern editing, point-cloud- and silhouette-conditioned garment generation. Our project website is at https://garment-particles.github.io .