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Adversarial Learning

1235 directly classified papers

Papers per year

Papers

ColorFool: Semantic Adversarial Colorization CVPR 2020
Polishing Decision-Based Adversarial Noise With a Customized Sampling CVPR 2020
Single-Step Adversarial Training With Dropout Scheduling CVPR 2020
Universal Litmus Patterns: Revealing Backdoor Attacks in CNNs CVPR 2020
Transferable, Controllable, and Inconspicuous Adversarial Attacks on Person Re-identification With Deep Mis-Ranking CVPR 2020
Towards Verifying Robustness of Neural Networks Against A Family of Semantic Perturbations CVPR 2020
Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization CVPR 2020
Learn2Perturb: An End-to-End Feature Perturbation Learning to Improve Adversarial Robustness CVPR 2020
Modeling Biological Immunity to Adversarial Examples CVPR 2020
Towards Achieving Adversarial Robustness by Enforcing Feature Consistency Across Bit Planes CVPR 2020
Robustness Guarantees for Deep Neural Networks on Videos CVPR 2020
VIBE: Video Inference for Human Body Pose and Shape Estimation CVPR 2020
Understanding Adversarial Examples From the Mutual Influence of Images and Perturbations CVPR 2020
Robust Superpixel-Guided Attentional Adversarial Attack CVPR 2020
x-Vectors Meet Adversarial Attacks: Benchmarking Adversarial Robustness in Speaker Verification INTERSPEECH 2020
Inaudible Adversarial Perturbations for Targeted Attack in Speaker Recognition INTERSPEECH 2020
The Attacker’s Perspective on Automatic Speaker Verification: An Overview INTERSPEECH 2020
Defense for Black-Box Attacks on Anti-Spoofing Models by Self-Supervised Learning INTERSPEECH 2020
Dual-Adversarial Domain Adaptation for Generalized Replay Attack Detection INTERSPEECH 2020
Adversarial Separation Network for Speaker Recognition INTERSPEECH 2020
Improving the Speaker Identity of Non-Parallel Many-to-Many Voice Conversion with Adversarial Speaker Recognition INTERSPEECH 2020
Generating Label Cohesive and Well-Formed Adversarial Claims EMNLP 2020
Detecting Word Sense Disambiguation Biases in Machine Translation for Model-Agnostic Adversarial Attacks EMNLP 2020
Don’t take “nswvtnvakgxpm” for an answer –The surprising vulnerability of automatic content scoring systems to adversarial input COLING 2020
I Am Guessing You Can't Recognize This: Generating Adversarial Images for Object Detection Using Spatial Commonsense (Student Abstract) AAAI 2020