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Survey details periocular biometrics for media forensics and disinformation detection

A new survey paper explores the use of periocular soft biometrics for applications in multimedia forensics and disinformation detection. The paper details demographic attribute estimation from periocular images, covering datasets, deep learning methods, and the current state of gender, age, and ethnicity prediction. It also discusses challenges such as dataset bias, fairness, and the need for forensic-oriented benchmarks. AI

IMPACT This research could enhance the accuracy and scope of multimedia forensics and disinformation detection systems.

RANK_REASON This is a survey paper published on arXiv detailing research on periocular biometrics. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CV →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Survey details periocular biometrics for media forensics and disinformation detection

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This is a survey paper published on arXiv detailing research on periocular biometrics. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CV TIER_1 English(EN) · Fernando Alonso-Fernandez, Kevin Hernandez-Diaz, Josef Bigun ·

    Periocular Soft Biometrics: A Survey and Applications to Multimedia Forensics and Disinformation Detection

    arXiv:2608.14701v1 Announce Type: new Abstract: Soft-biometric attributes such as gender, age, and ethnicity provide valuable ancillary evidence when full identity recognition is not feasible, supporting applications in forensic investigation, identity verification, surveillance,…