12 citations · 31 across the 6 of their papers we have counts for
16 papers · 1 filter
Robustness-via-Synthesis: Robust Training with Generative Adversarial Perturbations
Inci M. Baytas, Debayan Deb
Upon the discovery of adversarial attacks, robust models have become obligatory for deep learning-based systems. Adversarial training with first-order attacks has been one of the m…
Biometrics: Trust, but Verify
Anil K. Jain, Debayan Deb, Joshua J. Engelsma
Over the past two decades, biometric recognition has exploded into a plethora of different applications around the globe. This proliferation can be attributed to the high levels of…
Unified Detection of Digital and Physical Face Attacks
Debayan Deb, Xiaoming Liu, Anil K. Jain
State-of-the-art defense mechanisms against face attacks achieve near perfect accuracies within one of three attack categories, namely adversarial, digital manipulation, or physica…
FaceGuard: A Self-Supervised Defense Against Adversarial Face Images
Debayan Deb, Xiaoming Liu, Anil K. Jain
Prevailing defense mechanisms against adversarial face images tend to overfit to the adversarial perturbations in the training set and fail to generalize to unseen adversarial atta…
Infant-ID: Fingerprints for Global Good
Joshua J. Engelsma, Debayan Deb, Kai Cao +3
In many of the least developed and developing countries, a multitude of infants continue to suffer and die from vaccine-preventable diseases and malnutrition. Lamentably, the lack…
Look Locally Infer Globally: A Generalizable Face Anti-Spoofing Approach
Debayan Deb, Anil K. Jain
State-of-the-art spoof detection methods tend to overfit to the spoof types seen during training and fail to generalize to unknown spoof types. Given that face anti-spoofing is inh…