---
language:
- en
license: cc-by-4.0
size_categories:
- 1K<n<10K
pretty_name: ClothTransformer Dataset
viewer: false
task_categories:
- other
tags:
- cloth-simulation
- physics
- mesh
- 3d
- simulation
---

# ClothTransformer Dataset

[Paper (arXiv:2605.27852)](https://arxiv.org/abs/2605.27852) | [Project Page](https://yucrazing.github.io/clothtransformer/) | [Code](https://github.com/YuCrazing/ClothTransformer)

Official dataset of **ClothTransformer: Unified Latent-Space Transformers for Scalable
Cloth Simulation**. It contains **2,056 penetration-free cloth simulation trajectories**
(240 frames each, **493,440 frames** in total, ~33 GB) across three scenarios: free-fall
collision onto diverse objects, garments on animated human bodies, and robotic cloth
manipulation. Each trajectory is a cloth mesh interacting with a static or moving
collider, stored as one self-contained NumPy `.npz` file.

## Preview

| Human Garment | Robotic Manipulation | Diverse Object Collision |
|:---:|:---:|:---:|
| <video src="https://huggingface.co/datasets/YuCrazing1/ClothTransformer-dataset/resolve/main/videos/human_garment.mp4" width="240" controls autoplay muted loop playsinline></video> | <video src="https://huggingface.co/datasets/YuCrazing1/ClothTransformer-dataset/resolve/main/videos/robotic_manipulation.mp4" width="240" controls autoplay muted loop playsinline></video> | <video src="https://huggingface.co/datasets/YuCrazing1/ClothTransformer-dataset/resolve/main/videos/diverse_object_collision.mp4" width="240" controls autoplay muted loop playsinline></video> |

## Dataset Structure

```
ClothTransformer-dataset/
├── sims_collision_all_static_1k/   # Diverse Object Collision: cloth dropped onto a static object (1,000 sims)
├── sims_garment_anim_all/          # Human Garment: garment worn by an animated body              (56 sims)
└── sims_grasp_all_case1/           # Robotic Manipulation: cloth grasped by a robotic gripper     (1,000 sims)
```

Each simulation `i` comes with two files:

| File | Content |
|---|---|
| `sim_{i:05d}.npz` | The full simulation arrays (see below). **This is all you need.** |
| `sim_{i:05d}_processed_cloth_00000_uv.*` | Cloth rest mesh with UVs — `.obj` in `sims_garment_anim_all`, Houdini `.bgeo.sc` in the other two scenarios. Optional: the same geometry is already inside the `.npz`. |

The array schema is identical across scenarios. Mesh resolution varies per sample —
always read shapes from the file.

| Subset | Cloth #Verts | Cloth #Faces | Collider #Faces | Sequences | Frames |
|---|---|---|---|---|---|
| Human Garment | 1k–3.6k | 2k–7.1k | 1k–5.1k | 56 | 13,440 |
| Robotic Manipulation | 1k–4k | 1.9k–7.9k | 0.6k | 1,000 | 240,000 |
| Diverse Object Collision | 3.6k | 7k | 1k–4k | 1,000 | 240,000 |
| **Total** | 1k–4k | 1.9k–7.9k | 0.6k–5.1k | **2,056** | **493,440** |

## Data Fields

Notation: `N_v` / `N_c` = cloth / collider vertex count, `F` / `E` = triangle / edge
counts, `T = 240` frames at `dt = 1/60 s` (4 s). Coordinates are world units, Y-up.
Velocity fields store **per-frame displacements**; divide by `dt` for physical velocity.

| Key | Shape | Dtype | Description |
|---|---|---|---|
| `initial` | `(N_v, 6)` | float64 | Cloth rest state: `[0:3]` rest position (equals `traj[0]`), `[3:6]` UV as `(u, v, 0)`. |
| `traj` | `(T, N_v, 3)` | float32 | Cloth vertex positions per frame. |
| `traj_vel` | `(T, N_v, 3)` | float32 | Cloth per-frame displacement: `traj_vel[t] == traj[t] − traj[t−1]`. |
| `triangles` | `(F_cloth, 3)` | int32 | Cloth triangle vertex indices (0-based). |
| `edges` | `(E_cloth, 2)` | int32 | Cloth edge vertex-index pairs. |
| `collision_vertices` | `(T, N_c, 3)` | float32 | Collider vertex positions per frame (constant for static colliders). |
| `collision_vel` | `(T, N_c, 3)` | float32 | Collider per-frame displacement. |
| `collision_triangles` | `(F_col, 3)` | int32 | Collider triangle vertex indices. |
| `collision_edges` | `(E_col, 2)` | int32 | Collider edge vertex-index pairs. |
| `collision` | `(T, F_col, 9)` | float32 | Redundant convenience field: per-frame triangle corner positions, exactly `collision_vertices` gathered by `collision_triangles`. |

Topology is fixed over time within a sample and differs between samples.

## Usage

```python
import numpy as np

data = np.load("sims_collision_all_static_1k/sim_00000.npz")  # no allow_pickle needed
cloth_pos = data["traj"]                       # (240, N_v, 3)
cloth_vel = data["traj_vel"] / (1 / 60)        # world units per second

# Reconstruct the redundant `collision` field from raw arrays:
cv, tri = data["collision_vertices"], data["collision_triangles"]
collision = cv[:, tri.reshape(-1)].reshape(cv.shape[0], -1, 9)
```

See [`example_load_dataset.py`](example_load_dataset.py) for a complete script that
loads a sample and exports frames to OBJ.

## Data Generation

All trajectories are ground-truth simulations of the Baraff–Witkin cloth model produced
with [GIPC](https://doi.org/10.1145/3643028) (Huang et al., ACM TOG 2024), a
penetration-free GPU solver based on incremental potential contact. The dataset is
**strictly intersection-free**, making it suitable for training with Continuous
Collision Detection (CCD) losses. Material parameters: stretching Young's modulus
`1e6 Pa`, bending Young's modulus `1e5 Pa`, Poisson's ratio `0.49`, shear stiffness
`5e6 Pa`, density `200 g/m²`, friction coefficient `0.4`.

| Subset | Cloth meshes | Collider |
|---|---|---|
| Human Garment | T-shirts and skirts | Animated [SMPL](https://smpl.is.tue.mpg.de/) avatars; all motions (walking, running, dancing, jumping, etc.) generated with [Make-It-Animatable](https://arxiv.org/abs/2411.18197), no external mocap data involved |
| Robotic Manipulation | 1,000+ garments from the [Dataset of 3D Garments with Sewing Patterns](https://doi.org/10.5281/zenodo.5267549) | Robotic gripper |
| Diverse Object Collision | Square cloth sheets | 1,000+ rigid objects sampled from [Objaverse](https://objaverse.allenai.org/) |

In the paper, each subset is split into train / validation / test sets at an 8:1:1 ratio.

## License

Released under **CC BY 4.0**. Portions of the underlying geometry derive from
third-party assets with their own terms:

- **SMPL-Body** ([CC BY 4.0](https://smpl.is.tue.mpg.de/license.html)) — human body
  colliders, courtesy of the Max Planck Institute for Intelligent Systems.
- **[Make-It-Animatable](https://huggingface.co/jasongzy/Make-It-Animatable)**
  ([Apache 2.0](https://www.apache.org/licenses/LICENSE-2.0)) — used to generate the
  body motions in the Human Garment subset.
- **Dataset of 3D Garments with Sewing Patterns**
  ([CC BY 4.0](https://doi.org/10.5281/zenodo.5267549)) — garment meshes in the
  Robotic Manipulation subset.
- **Objaverse** ([ODC-BY 1.0](https://opendatacommons.org/licenses/by/1-0/)) — collider
  meshes in the Diverse Object Collision subset; each object retains its own Creative
  Commons license as recorded in the Objaverse metadata.

## Citation

```bibtex
@article{zhang2026clothtransformer,
  title   = {ClothTransformer: Unified Latent-Space Transformers for Scalable Cloth Simulation},
  author  = {Zhang, Yu and Shao, Yidi and Ouyang, Wenqi and Lan, Yushi and Liang, Zhexin and Wu, Chengrui and Xu, Xudong and Pan, Xingang},
  journal = {arXiv preprint arXiv:2605.27852},
  year    = {2026}
}
```