← Learning Types
Deep Learning › Learning Types ›

Adversarial Learning

2063 directly classified papers

Papers per year

Papers

SSCL: Adversarially Guided Image Compression via Semantic and Spectral Consistency Learning AAAI 2026
Phased One-Step Adversarial Equilibrium for Video Diffusion Models AAAI 2026
SVS-GAN for Semantic Synthesis of Traffic Videos for Autonomous Driving WACV 2026
Grimm: A Plug-and-Play Perturbation Rectifier for Graph Neural Networks Defending Against Poisoning Attacks AAAI 2025
Towards Adversarially Robust Dataset Distillation by Curvature Regularization AAAI 2025
Highly Imperceptible Black-Box Graph Injection Attacks with Reinforcement Learning AAAI 2025
FaceShield: Defending Facial Image against Deepfake Threats ICCV 2025
When and Where do Data Poisons Attack Textual Inversion? ICCV 2025
Hate in Plain Sight: On the Risks of Moderating AI-Generated Hateful Illusions ICCV 2025
Boosting Adversarial Transferability via Residual Perturbation Attack ICCV 2025
NullSwap: Proactive Identity Cloaking Against Deepfake Face Swapping ICCV 2025
Ph-GAN: Physics-Inspired GAN for Generating SAR Images Under Limited Data ICCV 2025
Failure Cases Are Better Learned But Boundary Says Sorry: Facilitating Smooth Perception Change for Accuracy-Robustness Trade-Off in Adversarial Training ICCV 2025
PBCAT: Patch-Based Composite Adversarial Training against Physically Realizable Attacks on Object Detection ICCV 2025
AdvERSEM: Adversarial Robustness Testing and Training of LLM-based Groundedness Evaluators via Semantic Structure Manipulation EMNLP 2025
DEAL: Data-Efficient Adversarial Learning for High-Quality Infrared Imaging CVPR 2025
D^3: Scaling Up Deepfake Detection by Learning from Discrepancy CVPR 2025
Chain of Attack: On the Robustness of Vision-Language Models Against Transfer-Based Adversarial Attacks CVPR 2025
Advancing Adversarial Robustness in GNeRFs: The IL2-NeRF Attack CVPR 2025
Exploring Semantic Feature Discrimination for Perceptual Image Super-Resolution and Opinion-Unaware No-Reference Image Quality Assessment CVPR 2025
Harnessing Global-Local Collaborative Adversarial Perturbation for Anti-Customization CVPR 2025
Pretend Benign: A Stealthy Adversarial Attack by Exploiting Vulnerabilities in Cooperative Perception ICCV 2025
Improving Transferable Targeted Attacks with Feature Tuning Mixup CVPR 2025
Towards Million-Scale Adversarial Robustness Evaluation With Stronger Individual Attacks CVPR 2025
MOS-Attack: A Scalable Multi-objective Adversarial Attack Framework CVPR 2025