Parsing IKEA Objects: Fine Pose Estimation
Abstract
We address the problem of localizing and estimating the fine-pose of objects in the image with exact 3D models. Our main focus is to unify contributions from the 1970s with recent advances in object detection: use local keypoint detectors to find candidate poses and score global alignment of each candidate pose to the image. Moreover, we also provide a new dataset containing fine-aligned objects with their exactly matched 3D models, and a set of models for widely used objects. We also evaluate our algorithm both on object detection and fine pose estimation, and show that our method outperforms state-of-the art algorithms.
Cite
Text
Lim et al. "Parsing IKEA Objects: Fine Pose Estimation." International Conference on Computer Vision, 2013. doi:10.1109/ICCV.2013.372Markdown
[Lim et al. "Parsing IKEA Objects: Fine Pose Estimation." International Conference on Computer Vision, 2013.](https://mlanthology.org/iccv/2013/lim2013iccv-parsing/) doi:10.1109/ICCV.2013.372BibTeX
@inproceedings{lim2013iccv-parsing,
title = {{Parsing IKEA Objects: Fine Pose Estimation}},
author = {Lim, Joseph J. and Pirsiavash, Hamed and Torralba, Antonio},
booktitle = {International Conference on Computer Vision},
year = {2013},
doi = {10.1109/ICCV.2013.372},
url = {https://mlanthology.org/iccv/2013/lim2013iccv-parsing/}
}