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metadata 
license: cc-by-4.0
Modalities:
  - Image
  - 3D
language:
  - en
size_categories:
  - 1K<n<10K
tags:
  - 3d
  - blender
  - vision
  - template
pretty_name: FoldNet

FoldNet Dataset

Teaser Image

Project Page Paper Github Code

FoldNet is a high-fidelity synthetic dataset featuring over 4,000 unique meshes across four distinct garment categories. Designed to support a wide range of downstream applications—including robotic folding and cloth manipulation—FoldNet provides physically plausible geometries paired with photorealistic textures.

🔑 Key Features

  • Diverse Cloth Categories: including tshirt, trousers, vest and hoodie.
  • High Quality Mesh:
    • Watertight and manifold meshes.
    • No self-intersections.
    • Configurable resolution with adjustable vertex density and face sizing.
  • Diverse and Realistic Textures: High-quality textures procedurally generated via Stable-Diffusion-3.5
  • Rich Annotation:
    • Automatically labeled manipulable keypoints for robotic interaction.
    • Pre-computed UV mapping for seamless texturing.
  • Highly Scalable: A robust procedural framework capable of generating an infinite variety of plausible garment shapes.

🔥 Get started

To download the full dataset, you can use the following code. If you encounter any issues, please refer to the official Hugging Face documentation.

# Make sure you have git-lfs installed (https://git-lfs.com)
git lfs install

# When prompted for a password, use an access token with write permissions.
# Generate one from your settings: https://huggingface.co/settings/tokens
git clone https://huggingface.co/datasets/Bowie375/FoldNet

# If you want to clone without large files - just their pointers
GIT_LFS_SKIP_SMUDGE=1 git clone https://huggingface.co/datasets/Bowie375/FoldNet

🗂️ Dataset Structure

Under mesh directory, we provide raw cloth meshes with default texture:

mesh
├── tshirt_sp                                  # category
│   ├── 0
│   │   ├── mesh.obj                           # generated mesh
│   │   ├── mesh.key.obj                       # the same mesh with keypoints marked red
│   │   ├── mesh_info.json                     # the configurations of the mesh, like edge length and keypoint index
│   │   ├── material.mtl
│   │   ├── material.png                       # default texture
│   ├── 1
│   │   └── ...
│   ├── ...
├── trousers
│   ├── ...
├── vest_close
│   ├── ...
├── hooded_close
│   ├── ...

🛠️ Dataset Creation

FoldNet features a fully automated end-to-end data generation pipeline. Our framework procedurally synthesizes garment geometries, applies AI-driven texturing, and generates ground-truth annotations without human intervention.

For technical implementation details, source code, and step-by-step instructions to reproduce the dataset, please visit the FoldNet GitHub Repository.

📅 TODO List

  • [2026.2] Released: 4k synthetic 3D garment assets (across 4 cloth categories). The directory is mesh.
  • To be released: textured cloth data.

Citation 

@article{11359673,
  author={Chen, Yuxing and Xiao, Bowen and Wang, He},
  journal={IEEE Robotics and Automation Letters}, 
  title={FoldNet: Learning Generalizable Closed-Loop Policy for Garment Folding via Keypoint-Driven Asset and Demonstration Synthesis}, 
  year={2026},
  volume={},
  number={},
  pages={1-8},
  keywords={Clothing;Geometry;Imitation learning;Annotations;Trajectory;Training;Synthetic data;Pipelines;Grasping;Filtering;Bimanual manipulation;deep learning for visual perception;deep learning in grasping and manipulation},
  doi={10.1109/LRA.2026.3656770}}