Completing 3D Object Shape from One Depth Image
Abstract
Our goal is to recover a complete 3D model from a depth image of an object. Existing approaches rely on user interaction or apply to a limited class of objects, such as chairs. We aim to fully automatically reconstruct a 3D model from any category. We take an exemplar-based approach: retrieve similar objects in a database of 3D models using view-based matching and transfer the symmetries and surfaces from retrieved models. We investigate completion of 3D models in three cases: novel view (model in database); novel model (models for other objects of the same category in database); and novel category (no models from the category in database).
Cite
Text
Rock et al. "Completing 3D Object Shape from One Depth Image." Conference on Computer Vision and Pattern Recognition, 2015. doi:10.1109/CVPR.2015.7298863Markdown
[Rock et al. "Completing 3D Object Shape from One Depth Image." Conference on Computer Vision and Pattern Recognition, 2015.](https://mlanthology.org/cvpr/2015/rock2015cvpr-completing/) doi:10.1109/CVPR.2015.7298863BibTeX
@inproceedings{rock2015cvpr-completing,
title = {{Completing 3D Object Shape from One Depth Image}},
author = {Rock, Jason and Gupta, Tanmay and Thorsen, Justin and Gwak, JunYoung and Shin, Daeyun and Hoiem, Derek},
booktitle = {Conference on Computer Vision and Pattern Recognition},
year = {2015},
doi = {10.1109/CVPR.2015.7298863},
url = {https://mlanthology.org/cvpr/2015/rock2015cvpr-completing/}
}