Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models

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Deform360 is a massive multi-view visuotactile dataset for deformable-object research, featuring 198 daily-life objects, 1,980 interaction sequences, and over 215 hours of observations from 41 surround-view cameras and bimanual tactile grippers to capture both global motion and contact-induced local deformations.

Installation

To load and interact with the dataset, install the helper library:

git clone https://github.com/lhy0807/deform360.git
cd deform360
pip install -e ".[all]"

Sample Usage

Loading Aligned Multi-View Data

The MultiViewDataset class returns synchronized RGB frames, calibration, and the common timestamp. It is compatible with the Dataset protocol but does not require PyTorch.

from deform360 import MultiViewDataset

episode = "/path/to/deform360_data/processed/001-rope/episode_0000"
with MultiViewDataset(episode) as dataset:
    sample = dataset[0]

sample["images"]         # list[(H,W,3) uint8 RGB]
sample["intrinsics"]     # list[(3,3)]
sample["extrinsics"]     # list[(4,4) camera-to-world]
sample["cameras"]        # camera names
sample["timestamp_us"]   # shared Unix timestamp in microseconds

Loading Aligned Tactile Data

Load all synchronized tactile grids at the same frame index with:

from deform360 import TactileDataset

episode = "/path/to/deform360_data/processed/001-rope/episode_0000"
with TactileDataset(episode) as tactile:
    frame = tactile[0]        # sensor name -> (16,32) float32

Citation

If you find Deform360 useful, please cite:

@inproceedings{li2026deform360,
  title     = {Deform360: A Massive Multi-view Visuotactile Dataset for Deformable World Models},
  author    = {Li, Hongyu and Fu, Wanjia and Cong, Xiaoyan and Li, Zekun and Huang, Binghao and Jiang, Hanxiao and He, Xintong and Liang, Yiqing and Fu, Rao and Lu, Tao and Sridhar, Srinath and Smith, Kevin A. and Konidaris, George and Li, Yunzhu},
  booktitle = {European Conference on Computer Vision (ECCV)},
  year      = {2026}
}