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OakInk: A Large-scale Knowledge Repository for Understanding Hand-Object Interaction


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News

Jul 26, 2022 Tink code has been made public.
Jun 28, 2022 OakInk version 2 (public) has been released.:sparkles:
We release oakink toolkit -- a Python package that provides data loading and visualization.
Mar 03, 2022 OakInk has been accepted by CVPR 2022.

Abstract

Learning how humans manipulate objects requires machines to acquire knowledge from two perspectives: one for understanding object affordances and the other for learning human's interactions based on the affordances. Even though these two knowledge bases are crucial, we find that current databases lack a comprehensive awareness of them.

In this work, we propose a multi-modal and rich-annotated knowledge repository, oakink, for visual and cognitive understanding of hand-object interactions. We start to collect 1,800 common household objects and annotate their affordances to construct the first knowledge base: oak. Given the affordance, we record rich human interactions with 100 selected objects in oak. Finally, we transfer the interactions on the 100 recorded objects to their virtual counterparts through a novel method: tink. The recorded and transferred hand-object interactions constitute the second knowledge base: ink. As a result, oakink contains 50,000 distinct affordance-aware and intent-oriented hand-object interactions.

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Downloads

Download from Dropbox.

OakInk-Image -- image-based subset.


OakInk-Shape -- shape-based subset.

After downloading all the above .zip files, you need to arrange them in the following structure:
  
    ├── image
    │   ├── anno.zip
    │   ├── obj.zip
    │   └── stream_zipped
    │       ├── oakink_image_v2.z01
    │       ├── ...
    │       ├── oakink_image_v2.z10
    │       └── oakink_image_v2.zip
    └── shape
        ├── metaV2.zip
        ├── OakInkObjectsV2.zip
        ├── oakink_shape_v2.zip
        └── OakInkVirtualObjectsV2.zip
  

Code

OakInk Toolkit -- A Python package that provides data loading and visualization for the OakInk dataset.
Tink -- For transferring hand pose from source object to target objects.

Citation

If you find OakInk dataset and oikit useful for your research, please considering cite us:


@InProceedings{YangCVPR2022OakInk,
    author = {Yang, Lixin and Li, Kailin and Zhan, Xinyu and Wu, Fei and Xu, Anran and Liu, Liu and Lu, Cewu},
    title = {{OakInk}: A Large-Scale Knowledge Repository for Understanding Hand-Object Interaction},
    booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    year = {2022},
}

Contact

For further information, please contact siriusyang[at]sjtu[dot]edu[dot]cn