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DeformingThings4D dataset

Video | Paper

DeformingThings4D is an synthetic dataset containing 1,972 animation sequences spanning 31 categories of humanoids and animals.

Animation file (.anime)

An animation example. Colors indicate dense correspondence

We store an animation sequence in the .anime file. The first frame is the canonical frame for which we store its triangle mesh. From the 2nd to the last frame, we store the 3D offsets of the mesh vertices.

#length         #type       #contents
|1              |int32      |nf: number of frames in the animation 
|1              |int32      |nv: number of vertices in the mesh (mesh topology fixed through frames)
|1              |int32      |nt: number of triangle face in the mesh
|nv*3           |float32    |vertice data of the 1st frame (3D positions in x-y-z-order)
|nt*3           |int32      |triangle face data of the 1st frame
|(nf-1)*nv*3    |float32    |3D offset data from the 2nd to the last frame

1,972 animations

Currently, we provide 200 animations for humanoids and 1772 animations for animals. The followings show the structure of the dataset. The screenshots show the animations in the dataset.

|---|--humanoids (200 animations, 34228 frames)
    |   |--clarie_run  #a animation folder [objectID]_[ActionID])
    |       |--clarie_run.anime # animation file, storing per-frame shape and
    |       |--screenshots # screenshots of animation
    |       |--clarie_run.fbx # raw blender animation file, only available for humanoids
    |--animals (1772 animations, 88137 frames)

Download Data google form

Currently, we provide the .anime files for all 1972 animations. If you would like to download the DeformingThings4D data, please fill out this google form, and, once accepted, we will send you the link to download the data.

We can also provide blender-generated scene flow & RGBD sequences and volume data upon request. You can also generate these data from the .anime files using the Blender scripts.

Use case of the dataset

The dataset is designed to tackle the following tasks using data-driven approaches

• Scene flow estimation,
• Deformable point cloud matching
• Non-rigid tracking/registration
• Shape and motion completion
• Learning riggings from observation
• Generic non-rigid reconstruction

The following shows real-world scene flow estimation and 4dcomplete results using models that are trained with this dataset.

Citation

If you use DeformingThings4D data or code please cite:

@article{li20214dcomplete, 
    title={4dcomplete: Non-rigid motion estimation beyond the observable surface.}, 
    author={Yang Li, Hikari Takehara, Takafumi Taketomi, Bo Zheng, and Matthias Nießner},
    journal={IEEE International Conference on Computer Vision (ICCV)},
    year={2021}
}

License

The data is released under DeformingThings4D Terms of Use, and the code is release under a non-comercial creative commons license.