Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation

26 October 2023

Papers citing "Uncertainty-weighted Loss Functions for Improved Adversarial Attacks on Semantic Segmentation"

5 / 5 papers shown

Title
Pixel-wise Gradient Uncertainty for Convolutional Neural Networks applied to Out-of-Distribution Segmentation Kira Maag Tobias Riedlinger UQCV 30 7 0 13 Mar 2023
Certified Defences Against Adversarial Patch Attacks on Semantic Segmentation Maksym Yatsura K. Sakmann N. G. Hua Matthias Hein J. H. Metzen AAML 50 17 0 13 Sep 2022
The Vulnerability of Semantic Segmentation Networks to Adversarial Attacks in Autonomous Driving: Enhancing Extensive Environment Sensing Andreas Bär Jonas Löhdefink Nikhil Kapoor Serin Varghese Fabian Hüger Peter Schlicht Tim Fingscheidt AAML 95 33 0 11 Jan 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 256 3,108 0 04 Nov 2016
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning Y. Gal Zoubin Ghahramani UQCV BDL 247 9,109 0 06 Jun 2015