Adversarial Vision Challenge
Wieland Brendel, Jonas Rauber, Alexey Kurakin, Nicolas Papernot, Behar Veliqi, Marcel Salathé, Sharada P. Mohanty, Matthias Bethge
arXiv:1808.01976v261 citations
Originality Synthesis-oriented
AI Analysis
It addresses the problem of improving adversarial robustness in machine vision for researchers and practitioners, but is incremental as it builds on existing competition frameworks.
The paper describes the NIPS 2018 Adversarial Vision Challenge, a competition aimed at advancing robust machine vision models and general adversarial attacks, with no specific results or numbers reported.
The NIPS 2018 Adversarial Vision Challenge is a competition to facilitate measurable progress towards robust machine vision models and more generally applicable adversarial attacks. This document is an updated version of our competition proposal that was accepted in the competition track of 32nd Conference on Neural Information Processing Systems (NIPS 2018).