Object Wake-up: 3D Object Rigging from a Single Image

Abstract

Given a single chair image, could we wake it up by reconstructing its 3D shape and skeleton, as well as animating its plausible articulations and motions, similar to that of human modeling? It is a new problem that not only goes beyond image-based object reconstruction but also involves articulated animation of generic objects in 3D, which could give rise to numerous downstream augmented and virtual reality applications. In this paper, we propose an automated approach to tackle the entire process of reconstruct such generic 3D objects, rigging and animation, all from single images. A two-stage pipeline has thus been proposed, which specifically contains a multi-head structure to utilize the deep implicit functions for skeleton prediction. Two in-house 3D datasets of generic objects with high-fidelity rendering and annotated skeletons have also been constructed. Empirically our approach demonstrated promising results; when evaluated on the related sub-tasks of 3D reconstruction and skeleton prediction, our results surpass those of the state-of-the-arts by a noticeable margin. Our code and datasets are made publicly available at the dedicated project website.

Cite

Text

Yang et al. "Object Wake-up: 3D Object Rigging from a Single Image." Proceedings of the European Conference on Computer Vision (ECCV), 2022. doi:10.1007/978-3-031-20086-1_18

Markdown

[Yang et al. "Object Wake-up: 3D Object Rigging from a Single Image." Proceedings of the European Conference on Computer Vision (ECCV), 2022.](https://mlanthology.org/eccv/2022/yang2022eccv-object/) doi:10.1007/978-3-031-20086-1_18

BibTeX

@inproceedings{yang2022eccv-object,
  title     = {{Object Wake-up: 3D Object Rigging from a Single Image}},
  author    = {Yang, Ji and Zuo, Xinxin and Wang, Sen and Yu, Zhenbo and Li, Xingyu and Ni, Bingbing and Gong, Minglun and Cheng, Li},
  booktitle = {Proceedings of the European Conference on Computer Vision (ECCV)},
  year      = {2022},
  doi       = {10.1007/978-3-031-20086-1_18},
  url       = {https://mlanthology.org/eccv/2022/yang2022eccv-object/}
}