[CVPR'24 Highlight] HOLD: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video
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Zicong Fan, Maria Parelli, Maria Eleni Kadoglou, Muhammed Kocabas, Xu Chen, Michael J. Black, Otmar Hilliges
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- 2024.04.04: HOLD is awarded CVPR highlight!
- 2024.02.27: HOLD is accepted to CVPR'24! Working on code release!
This is a repository for HOLD, a method that jointly reconstructs hands and objects from monocular videos without assuming a pre-scanned object template.
HOLD can reconstruct 3D geometries of novel objects and hands:
Reconstructing object shapes from long-tailed distribution:
Support two hand interaction with objects:
✨CVPR 2023: ARCTIC is a dataset that includes accurate body/hand/object poses, multi-view RGB videos for articulated object manipulation. See our project page for details.
- Instructions to download in-the-wild videos from HOLD as well as preprocessed data
- Scripts to preprocess and train on custom videos
- A volumetric rendering framework to reconstruct dynamic hand-object interaction
- A generalized codebase for single and two hand interaction with objects
- A viewer to interact with the prediction
- Code to evaluate and compare with HOLD in HO3D
See more results on our project page!
@article{fan2024hold,
title={{HOLD}: Category-agnostic 3D Reconstruction of Interacting Hands and Objects from Video},
author={Fan, Zicong and Parelli, Maria and Kadoglou, Maria Eleni and Kocabas, Muhammed and Chen, Xu and Black, Michael J and Hilliges, Otmar},
booktitle = {Proceedings IEEE Conference on Computer Vision and Pattern Recognition (CVPR)},
year = {2024}
}For technical questions, please create an issue. For other questions, please contact the first author.
For commercial licensing, please contact ps-licensing@tue.mpg.de.
The authors would like to thank: Benjamin Pellkofer for IT/web support; Chen Guo, Egor Zakharov, Yao Feng, Artur Grigorev for insightful discussion; Yufei Ye for DiffHOI code release.