Document Type
Conference Proceeding
Publication Date
1-1-2020
Journal / Book Title
AAAI 2020 34th Aaai Conference on Artificial Intelligence
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.
DOI
10.1609/aaai.v34i10.7166
Montclair State University Digital Commons Citation
Garg, Anurag; Tandon, Niket; and Varde, Aparna S., "I Am Guessing You Can't Recognize This: Generating Adversarial Images for Object Detection Using Spatial Commonsense" (2020). Department of Computer Science Faculty Scholarship and Creative Works. 657.
https://digitalcommons.montclair.edu/compusci-facpubs/657
Rights
Copyright © 2020, Association for the Advancement of Artificial Intelligence. This conference paper has been made Open Access under license by the publisher.
Published Citation
Garg, A., Tandon, N., & Varde, A. S. (2020). I Am Guessing You Can’t Recognize This: Generating Adversarial Images for Object Detection Using Spatial Commonsense (Student Abstract). Proceedings of the AAAI Conference on Artificial Intelligence, 34(10), 13789-13790. https://doi.org/10.1609/aaai.v34i10.7166