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Adversarial Learning

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Papers

Adversarial VQA: A New Benchmark for Evaluating the Robustness of VQA Models ICCV 2021
S3VAADA: Submodular Subset Selection for Virtual Adversarial Active Domain Adaptation ICCV 2021
Feature Importance-Aware Transferable Adversarial Attacks ICCV 2021
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student Better ICCV 2021
Low Curvature Activations Reduce Overfitting in Adversarial Training ICCV 2021
Black-Box Detection of Backdoor Attacks With Limited Information and Data ICCV 2021
Semantic Concentration for Domain Adaptation ICCV 2021
SurfGen: Adversarial 3D Shape Synthesis With Explicit Surface Discriminators ICCV 2021
Batch Normalization Increases Adversarial Vulnerability and Decreases Adversarial Transferability: A Non-Robust Feature Perspective ICCV 2021
A Backdoor Attack Against 3D Point Cloud Classifiers ICCV 2021
Relating Adversarially Robust Generalization to Flat Minima ICCV 2021
Re-Energizing Domain Discriminator With Sample Relabeling for Adversarial Domain Adaptation ICCV 2021
Learning To Adversarially Blur Visual Object Tracking ICCV 2021
Knowledge-Enriched Distributional Model Inversion Attacks ICCV 2021
HIRE-SNN: Harnessing the Inherent Robustness of Energy-Efficient Deep Spiking Neural Networks by Training With Crafted Input Noise ICCV 2021
Detail Me More: Improving GAN's Photo-Realism of Complex Scenes ICCV 2021
PrimitiveNet: Primitive Instance Segmentation With Local Primitive Embedding Under Adversarial Metric ICCV 2021
Towards Understanding the Generative Capability of Adversarially Robust Classifiers ICCV 2021
Dynamic Divide-and-Conquer Adversarial Training for Robust Semantic Segmentation ICCV 2021
Membership Inference Attacks Are Easier on Difficult Problems ICCV 2021
Adversarial Attacks Are Reversible With Natural Supervision ICCV 2021
Information-Theoretic Regularization for Multi-Source Domain Adaptation ICCV 2021
Removing Adversarial Noise in Class Activation Feature Space ICCV 2021
Adversarial Example Detection Using Latent Neighborhood Graph ICCV 2021
Aha! Adaptive History-Driven Attack for Decision-Based Black-Box Models ICCV 2021