---
author:
- |
    Samuel Wilson\
    Queensland University of Technology\
    2 George St, Brisbane, QLD 4000, Australia\
    <span>timothy38@example.net</span>
- |
    Tobias Fischer\
    Queensland University of Technology\
    2 George St, Brisbane, QLD 4000, Australia\
    <span>timothy38@example.net</span>
- |
    Feras Dayoub\
    University of Adelaide\
    North Terrace, Adelaide, SA 5005, Australia\
    <span>timothy38@example.net</span>
- |
    Niko Sünderhauf\
    Queensland University of Technology\
    2 George St, Brisbane, QLD 4000, Australia\
    <span>timothy38@example.net</span>
bibliography:
- 'bib.bib'
title: |
    Noisy Inliers Make Great Outliers:\
    Out-of-Distribution Object Detection with Noisy Synthetic Outliers
---

**Acknowledgements:** The authors acknowledge continued support from the Queensland University of Technology (QUT) through the Centre for Robotics. TF was partially supported by funding from ARC Laureate Fellowship FL210100156 and Intel's Neuromorphic Computing Lab.

{'source': 'arXiv_out/2208'}