Segment (Almost) Nothing: Prompt-Agnostic Adversarial Attacks on Segmentation Models
Author:
Affiliation:
1. University of Tübingen,Tübingen AI Center,Germany
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10516617/10516618/10516626.pdf?arnumber=10516626
Reference35 articles.
1. Cospgd: a unified white-box adversarial attack for pixel-wise prediction tasks;Agnihotri,2023
2. On the Robustness of Semantic Segmentation Models to Adversarial Attacks
3. Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks;Croce;ICML,2020
4. Robust semantic segmentation: Strong adversarial attacks and fast training of robust models;Croce,2023
5. A Light Recipe to Train Robust Vision Transformers
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