Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?

Martin Mundt, Iuliia Pliushch, Sagnik Majumder, Visvanathan Ramesh

ICCVW 2019 pp. 753-757

doi:10.1109/ICCVW.2019.00098 /iccvw/2019/mundt2019iccvw-open/

Abstract

We present an analysis of predictive uncertainty based out-of-distribution detection for different approaches to estimate various models' epistemic uncertainty and contrast it with extreme value theory based open set recognition. While the former alone does not seem to be enough to overcome this challenge, we demonstrate that uncertainty goes hand in hand with the latter method. This seems to be particularly reflected in a generative model approach, where we show that posterior based open set recognition outperforms discriminative models and predictive uncertainty based outlier rejection, raising the question of whether classifiers need to be generative in order to know what they have not seen.

PDF ICCVW Semantic Scholar

Cite

Text

Mundt et al. "Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?." IEEE/CVF International Conference on Computer Vision Workshops, 2019. doi:10.1109/ICCVW.2019.00098

Markdown

[Mundt et al. "Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?." IEEE/CVF International Conference on Computer Vision Workshops, 2019.](https://mlanthology.org/iccvw/2019/mundt2019iccvw-open/) doi:10.1109/ICCVW.2019.00098

BibTeX

@inproceedings{mundt2019iccvw-open,
  title     = {{Open Set Recognition Through Deep Neural Network Uncertainty: Does Out-of-Distribution Detection Require Generative Classifiers?}},
  author    = {Mundt, Martin and Pliushch, Iuliia and Majumder, Sagnik and Ramesh, Visvanathan},
  booktitle = {IEEE/CVF International Conference on Computer Vision Workshops},
  year      = {2019},
  pages     = {753-757},
  doi       = {10.1109/ICCVW.2019.00098},
  url       = {https://mlanthology.org/iccvw/2019/mundt2019iccvw-open/}
}