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Found 5 papers, 0 papers with code
Hardening RGB-D Object Recognition Systems against Adversarial Patch Attacks
We empirically show that this defense improves the performances of RGB-D systems against adversarial examples even when they are computed ad-hoc to circumvent this detection mechanism, and that is also more effective than adversarial training.
Why Adversarial Reprogramming Works, When It Fails, and How to Tell the Difference
Adversarial reprogramming allows repurposing a machine-learning model to perform a different task.
3D Face Mask Presentation Attack Detection Based on Intrinsic Image Analysis
So, we propose a novel detection method for 3D face mask presentation attack by modeling reflectance differences based on intrinsic image analysis.
Face Presentation Attack Detection in Learned Color-liked Space
Face presentation attack detection (PAD) has become a thorny problem for biometric systems and numerous countermeasures have been proposed to address it.
Face Presentation Attack Detection
Generative Adversarial Network
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Local feature hierarchy for face recognition across pose and illumination
Accordingly we propose an end-to-end face recognition method to deal with pose and illumination simultaneously based on convolutional networks where the discriminative nonlinear features that are invariant to pose and illumination are extracted.
