Browsing NTNU Open by Author "Damer, Naser"

Now showing items 1-4 of 4

    • MIPGAN—Generating Strong and High Quality Morphing Attacks Using Identity Prior Driven GAN 

      Zhang, Haoyu; Venkatesh, Sushma; Ramachandra, Raghavendra; Raja, Kiran; Damer, Naser; Busch, Christoph (Journal article; Peer reviewed, 2021)
      Face morphing attacks target to circumvent Face Recognition Systems (FRS) by employing face images derived from multiple data subjects (e.g., accomplices and malicious actors). Morphed images can be verified against ...

    • Pixel-Level Face Image Quality Assessment for Explainable Face Recognition 

      Terhorst, Philipp; Huber, Marco; Damer, Naser; Kirchbuchner, Florian; Raja, Kiran; Kuijper, Arjan (Peer reviewed; Journal article, 2023)
      In this work, we introduce the concept of pixel-level gface image quality that determines the utility of single pixels in a face image for recognition. We propose a training-free approach to assess the pixel-level qualities ...

    • Pixel-wise supervision for presentation attack detection on identity document cards 

      Mudgalgundurao, Raghavendra; Schuch, Patrick; Raja, Kiran; Ramachandra, Raghavendra; Damer, Naser (Peer reviewed; Journal article, 2022)
      Identity documents (or IDs) play an important role in verifying the identity of a person with wide applications in banks, travel, video-identification services and border controls. Replay or photocopied ID cards can be ...

    • Template-Driven Knowledge Distillation for Compact and Accurate Periocular Biometrics Deep-Learning Models 

      Boutros, Fadi; Damer, Naser; Raja, Kiran; Kirchbuchner, Florian; Kuijper, Arjan (Peer reviewed; Journal article, 2022)
      This work addresses the challenge of building an accurate and generalizable periocular recognition model with a small number of learnable parameters. Deeper (larger) models are typically more capable of learning complex ...