# Iris Liveness Detection Competition (LivDet-Iris) -- The 2020 Edition

arXiv: https://arxiv.org/abs/2009.00749 · HTML: https://mlsanity.com/paper/2009.00749/

## Key facts

- Cited by 27 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 1 Sep 2020.

## Built on by (most cited first, 27 of 27)

- [Biometrics: Trust, but Verify](https://mlsanity.com/paper/2105.06625/) (2021)
- [Human-Aided Saliency Maps Improve Generalization of Deep Learning](https://mlsanity.com/paper/2105.03492/) (2021)
- [Deep Learning for Iris Recognition: A Survey](https://mlsanity.com/paper/2210.05866/) (2022)
- [Iris Presentation Attack Detection by Attention-based and Deep Pixel-wise Binary Supervision Network](https://mlsanity.com/paper/2106.14845/) (2021)
- [Iris Liveness Detection Competition (LivDet-Iris) -- The 2023 Edition](https://mlsanity.com/paper/2310.04541/) (2023)
- [Iris Liveness Detection using a Cascade of Dedicated Deep Learning Networks](https://mlsanity.com/paper/2105.14009/) (2021)
- [Teaching AI to Teach: Leveraging Limited Human Salience Data Into Unlimited Saliency-Based Training](https://mlsanity.com/paper/2306.05527/) (2023)
- [Towards Iris Presentation Attack Detection with Foundation Models](https://mlsanity.com/paper/2501.06312/) (2025)
- [MENTOR: Human Perception-Guided Pretraining for Increased Generalization](https://mlsanity.com/paper/2310.19545/) (2023)
- [Grains of Saliency: Optimizing Saliency-based Training of Biometric Attack Detection Models](https://mlsanity.com/paper/2405.00650/) (2024)
- [A Parametric Approach to Adversarial Augmentation for Cross-Domain Iris Presentation Attack Detection](https://mlsanity.com/paper/2412.07199/) (2024)
- [Introduction to Presentation Attack Detection in Iris Biometrics and Recent Advances](https://mlsanity.com/paper/2111.12465/) (2021)
- [Investigating Weight-Perturbed Deep Neural Networks With Application in Iris Presentation Attack Detection](https://mlsanity.com/paper/2311.12764/) (2023)
- [Synthetic Periocular Iris PAI from a Small Set of Near-Infrared-Images](https://mlsanity.com/paper/2107.12014/) (2021)
- [Intra and Cross-spectrum Iris Presentation Attack Detection in the NIR and Visible Domains](https://mlsanity.com/paper/2205.02573/) (2022)
- [A Multi-domain Image Translative Diffusion StyleGAN for Iris Presentation Attack Detection](https://mlsanity.com/paper/2510.14314/) (2025)
- [State Of The Art In Open-Set Iris Presentation Attack Detection](https://mlsanity.com/paper/2208.10564/) (2022)
- [Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognition](https://mlsanity.com/paper/2605.20735/) (2026)
- [DFCANet: Dense Feature Calibration-Attention Guided Network for Cross Domain Iris Presentation Attack Detection](https://mlsanity.com/paper/2111.00919/) (2021)
- [Iris Presentation Attack: Assessing the Impact of Combining Vanadium Dioxide Films with Artificial Eyes](https://mlsanity.com/paper/2311.12773/) (2023)
- [Training Better Deep Learning Models Using Human Saliency](https://mlsanity.com/paper/2410.16190/) (2024)
- [Task-conditioned Ensemble of Expert Models for Continuous Learning](https://mlsanity.com/paper/2504.08626/) (2025)
- [Almost Right: Making First-Layer Kernels Nearly Orthogonal Improves Model Generalization](https://mlsanity.com/paper/2504.16362/) (2025)
- [SAGE: Saliency-Guided Contrastive Embeddings](https://mlsanity.com/paper/2511.12744/) (2025)
- [Beyond Mortality: Advancements in Post-Mortem Iris Recognition through Data Collection and Computer-Aided Forensic Examination](https://mlsanity.com/paper/2603.26976/) (2026)
- [What's Old is New Again: Classical Dimensionality Reduction for Efficient Saliency-Guided Biometric Attack Detection](https://mlsanity.com/paper/2606.13528/) (2026)
- [Detecting Clear Contact Lenses for Iris Recognition: A Two-Stage Mask-Guided Attention Approach](https://mlsanity.com/paper/2608.08977/) (2026)

## Abstract (arXiv)

Launched in 2013, LivDet-Iris is an international competition series open to academia and industry with the aim to assess and report advances in iris Presentation Attack Detection (PAD). This paper presents results from the fourth competition of the series: LivDet-Iris 2020. This year's competition introduced several novel elements: (a) incorporated new types of attacks (samples displayed on a screen, cadaver eyes and prosthetic eyes), (b) initiated LivDet-Iris as an on-going effort, with a testing protocol available now to everyone via the Biometrics Evaluation and Testing (BEAT)(https://www.idiap.ch/software/beat/) open-source platform to facilitate reproducibility and benchmarking of new algorithms continuously, and (c) performance comparison of the submitted entries with three baseline methods (offered by the University of Notre Dame and Michigan State University), and three open-source iris PAD methods available in the public domain. The best performing entry to the competition reported a weighted average APCER of 59.10% and a BPCER of 0.46% over all five attack types. This paper serves as the latest evaluation of iris PAD on a large spectrum of presentation attack instruments.