Deep neural networks have proven to be highly effective in the face recognition task, as they can map raw samples into a discriminative high-dimensional representation space. However, understanding this complex space proves to be challenging for …
Occlusion is a common problem with biometric recognition in the wild. The generalization ability of CNNs greatly decreases due to the adverse effects of various occlusions. To this end, we propose a novel unified framework integrating the merits of …
Deep learning-based face recognition models are vulnerable to adversarial attacks. To curb these attacks, most defense methods aim to improve the robustness of recognition models against adversarial perturbations. However, the generalization …