Biometric Identification

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Overview

Biometric identification studies how to recognize or verify an individual from traits such as faces, fingerprints, irises, veins, voices, heart signals, gait, and interaction patterns. Approaches range from handcrafted features and minutiae matching to deep embeddings, metric learning, transformers, multimodal fusion, and synthetic-data generation. Evaluation increasingly considers open-set recognition and realistic shifts across sessions, devices, environments, and populations, using benchmarks that measure identification, verification, and spoof detection. A central challenge is making systems reliable under those shifts while protecting privacy and resisting attacks; high accuracy on controlled data alone does not establish safe deployment.

Latest papers

CardsList

129 papers10 papers in the last four weeks, down 23% on the four weeks before. 0.1% of all new papers.

  1. Illumination-Aware Contactless Fingerprint Spoof Detection via Paired Flash-Non-Flash Imaging

    Mar 18, 2026Roja Sahoo, Anoop NamboodiriBiometric IdentificationActive Sensing

    IIIT Hyderabad, Gachibowli, India

  2. Continual Few-shot Adaptation for Synthetic Fingerprint Detection

    Mar 15, 2026Joseph Geo Benjamin, Anil K. Jain, Karthik NandakumarFingerprint IdentificationBiometric Identification

    Michigan State University, East Lansing, MI, USA

  3. Deep Learning for Virtual Reality User Identification: A Benchmark

    Mar 14, 2026Davide Frizzo, Fabrizio Genilotti, David Petrovic +6Biometric IdentificationVirtual Reality

    University of Padova, Italy

  4. Self-Supervised Evolutionary Learning of Neurodynamic Progression and Identity Manifolds from EEG During Safety-Critical Decision Making

    Mar 7, 2026Xiaoshan Zhou, Carol C. Menassa, Vineet R. KamatSelf-Supervised LearningElectroencephalography

    Ph.D. Candidate, Dept. of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, 48109-2125. · Professor, Dept. of Civil and Environmental Engineering, University of Michigan, Ann Arbor, MI, 48109-2125.

  5. Detecting Cognitive Signatures in Typing Behavior for Non-Intrusive Authorship Verification

    Feb 26, 2026David CondreyAuthorship AttributionBiometric Identification

    Writerslogic, Inc.

  6. AHAN: Asymmetric Hierarchical Attention Network for Identical Twin Face Verification

    Feb 25, 2026Hoang-Nhat NguyenBiometric IdentificationFace Recognition

    Faculty of Mathematics and Informatics, Hanoi University of Science and Technology

  7. Advanced Acceptance Score: A Holistic Measure for Biometric Quantification

    Feb 17, 2026Aman Verma, Seshan Srirangarajan, Sumantra Dutta RoyBiometric Identification

    Dept. of Electrical Engineering, IIT Delhi, India · Dept. of Electrical Engineering and Bharti School of Telecommunications at IIT Delhi, India

  8. LEADER: Lightweight End-to-End Attention-Gated Dual Autoencoder for Robust Minutiae Extraction

    Feb 17, 2026Raffaele Cappelli, Matteo FerraraFingerprint IdentificationBiometric Identification

    Department of Computer Science and Engineering of the University of Bologna, Italy

  9. Hybrid Feature Learning for Handwriting Verification

    Nov 19, 2018Seyed Mohammad Abuzar Hashemi, Mihir Chauhan, Jun Chu +1Biometric IdentificationRepresentation Learning

    The Department of Computer Science and Engineering The State University of New York at Buffalo Buffalo, NY, USA