ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples

30 November 2018

Papers citing "ComDefend: An Efficient Image Compression Model to Defend Adversarial Examples"

7 / 7 papers shown

Title
Towards Model Resistant to Transferable Adversarial Examples via Trigger Activation Yi Yu Song Xia Xun Lin Chenqi Kong Wenhan Yang Shijian Lu Yap-Peng Tan Alex C. Kot AAML SILM 52 0 0 20 Apr 2025
Semantic-Aware Adversarial Training for Reliable Deep Hashing Retrieval Xu Yuan Zheng-Wei Zhang Xunguang Wang Lin Wu AAML 11 11 0 23 Oct 2023
Enhancing Adversarial Robustness via Score-Based Optimization Boya Zhang Weijian Luo Zhihua Zhang DiffM 8 11 0 10 Jul 2023
Sampling-based Fast Gradient Rescaling Method for Highly Transferable Adversarial Attacks Xuechun Han Anmin Liu Yifeng Xiong Yanbo Fan Kun He AAML 20 5 0 06 Apr 2022
Parallel Rectangle Flip Attack: A Query-based Black-box Attack against Object Detection Siyuan Liang Baoyuan Wu Yanbo Fan Xingxing Wei Xiaochun Cao AAML 13 69 0 22 Jan 2022
Adaptive Perturbation for Adversarial Attack Zheng Yuan Jie M. Zhang Zhaoyan Jiang Liangliang Li Shiguang Shan AAML 8 3 0 27 Nov 2021
Adversarial Machine Learning at Scale Alexey Kurakin Ian Goodfellow Samy Bengio AAML 253 3,102 0 04 Nov 2016