Publications

  1. DOOMGAN: High-Fidelity Dynamic Identity Obfuscation Ocular Generative Morphing (23 July 2025)
  2. ABRobOcular: Adversarial benchmarking and robustness analysis of datasets and tools for ocular-based user recognition (01 May 2025)
  3. Analyzing and mitigating bias of facial attribute classifiers using ChatGPT (01 January 2025)
  4. FineFACE: Fair Facial Attribute Classification Leveraging Fine-Grained Features (02 December 2024)
  5. A Self-Supervised Learning Pipeline for Demographically Fair Facial Attribute Classification (11 November 2024)
  6. Demographic Fairness and Accountability of Audio and Video-based Unimodal and Bi-modal Deepfake Detectors (30 January 2024)
  7. Demographic Bias Mitigation at Test-Time Using Uncertainty Estimation and Human-Machine Partnership (30 January 2024)
  8. Leveraging Diffusion and Flow Matching Models for Demographic Bias Mitigation of Facial Attribute Classifiers (30 November 2023)
  9. GBDF: Gender Balanced DeepFake Dataset Towards Fair DeepFake Detection (30 September 2023)
  10. A novel approach for bias mitigation of gender classification algorithms using consistency regularization (30 September 2023)
  11. ProActive DeepFake Detection using GAN-based Visible Watermarking (30 September 2023)
  12. An Examination and Comparison of Fairness of Face and Ocular Recognition Across Gender at NIR Spectrum (01 July 2023)
  13. Benchmarking Neural Network Compression Techniques for Ocular-Based User Authentication on Smartphones (06 April 2023)
  14. Is Facial Recognition Biased at Near-Infrared Spectrum as Well? (30 January 2023)
  15. Deep Generative Views to Mitigate Gender Classification Bias Across Gender-Race Groups (17 August 2022)
  16. Investigating Fairness of Ocular Biometrics Among Young, Middle-Aged, and Older Adults (13 October 2021)

Latest Updates

Feb 2, 2023
Final Results
Final Results

This page features condensed results of all the analysis that was done. Introduction Fairness evaluation studies across Biometric Modalities Fairness in Face Recognition Ocular : Motivation Research Objectives Covariates to be Studied Datasets Used Gender Classification Updates to Training Across Model - VIS Across Model - NIR Across Model - NIR (Cross Dataset) Across Databalance - VIS Across Databalance - NIR Across Race - VIS Across Age - VIS Across Modality - VIS Across Modality - NIR Across Device - VIS Across Lighting - VIS Across Spectrum Subject Verification Across Model - VIS Across Model - NIR Across Databalance - VIS Across Databalance - NIR Across Race - VIS Across Modality - VIS Across Modality - NIR Across Device - VIS Across Lighting - VIS Across Spectrum Summary

Dec 12, 2022
Results - Tables and Charts

Training Datasets VISOB - VIS, Gender, Subject, Race, Device, Lighting, Synthetic ND-IRIS - NIR, Gender, Subject UFPR - VIS, Gender, Subject, Age Notredame - NIR, VIS, Face, Ocular, Gender, Subject, Race Polyuiris - NIR, VIS, Subject Casia-Lamp - NIR, Subject Casia-Thousand - NIR, Subject FFHQ-Aging - VIS, Face, Ocular, Gender Casia-Syn - NIR, Subject, Synthetic Evaluation Datasets MOBIUS - VIS, Subject, Device, Light, Gaze, Quality, Gender, Age, Color VISA-IRIS - VIS, Subject, Gender, Face, Ocular IMP - NIR, VIS, Subject I-SOCIAL-DB - VIS, Subject Cross-Eyed - NIR, VIS, Subject UNAB - NIR, Subject, Gender, Makeup, Contacts Subject Verification Across Model - VIS Experiment ID Gender GMean GSTD IMean ISTD Sensitivity index (d') AUC J-Index MCC EER ZeroFMR FMR1000 FMR100 FMR20 FMR10 ZeroFNMR efficientnet_b0 male 0.
Jul 1, 2022
Intermediate Report

Introduction Fairness evaluation studies across Biometric Modalities Fairness in Face Recognition Ocular : Motivation Research Objectives Covariates to be Studied Datasets Used Gender Classification Across Models Across Models on UFPR Periocular - RGB Across Models on Notredame Ocular - NIR Across Varying Data Balances and Gender UFPR - RGB Notredame - NIR Across Age UFPR - RGB TABLE I: Accuracy of CNN-based Gender Classification on Left Ocular Region among Young (18 to 39 years), Middle (40 to 59 years) and Older Adults (60 to 79 years).
May 2, 2022
Preliminary Miscellaneous Results

Gender Classification Across Race on Ocular Training and Testing Dataset used - VISOB + Notredame Test Data is Limited and Imbalanced TABLE I: Gender Classification results across race groups - Ocular Datasets.
Mar 26, 2022
Notredame Preliminary Results
Notredame Preliminary Results

Dataset Gender Classification Results Subject Verification Results Subject Verification All Results Table Visualizations GradCAM GradCAM Guided GradCAM Guided GradCAM Occlusion Sensitivity Occlusion Sensitivity Vanilla Gradients Vanilla Gradients Integrated Gradients Integrated Gradients SmoothGrad -- Gradients x Input Gradients x Input Averaged Map × References Bibliography called, but no references

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