Generalized Data-free Universal Adversarial Perturbations
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Updated
Oct 5, 2018 - Python
Generalized Data-free Universal Adversarial Perturbations
Task-agnostic universal black-box attacks on computer vision neural network via procedural noise (CCS'19)
Universal Adversarial Perturbations (UAPs) for PyTorch
Official implementation of the ICCV2023 paper: Enhancing Generalization of Universal Adversarial Perturbation through Gradient Aggregation
PyTorch Implementation of Stereoscopic Universal Perturbations across Different Architectures and Datasets (CVPR 2022)
Generalized Data-free Universal Adversarial Perturbations in PyTorch
Universal Adversarial Audio Perturbations
Code implementing the experiments described in the NeurIPS 2018 paper "With Friends Like These, Who Needs Adversaries?".
Universal adversarial attack on NLP model
Evaluation of various defence mechanisms and various UAPs. Done as a part of GD-UAP.
Official implementation of "Resilience of Autonomous Vehicle Object Category Detections to Universal Adversarial Perturbations"
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