@inproceedings{7564c037eeea45acb3f19cfa79b8bac3,
title = "I Am Guessing You Can't Recognize This: Generating Adversarial Images for Object Detection Using Spatial Commonsense",
abstract = "Can we automatically predict failures of an object detection model on images from a target domain? We characterize errors of a state-of-the-art object detection model on the currently popular smart mobility domain, and find that a large number of errors can be identified using spatial commonsense. We propose CSK-SNIFFER, a system that automatically identifies a large number of such errors based on commonsense knowledge. Our system does not require any new annotations and can still find object detection errors with high accuracy (more than 80% when measured by humans). This work lays the foundation to answer exciting research questions on domain adaptation including the ability to automatically create adversarial datasets for target domain.",
author = "Anurag Garg and Niket Tandon and Varde, {Aparna S.}",
note = "Publisher Copyright: {\textcopyright} 2020 The Twenty-Fifth AAAI/SIGAI Doctoral Consortium (AAAI-20). All Rights Reserved.; 34th AAAI Conference on Artificial Intelligence, AAAI 2020 ; Conference date: 07-02-2020 Through 12-02-2020",
year = "2020",
language = "English",
series = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",
publisher = "AAAI press",
pages = "13789--13790",
booktitle = "AAAI 2020 - 34th AAAI Conference on Artificial Intelligence",
}