Browse State-of-the-Art › Iris Recognition
Iris Recognition
26 papers with code · 0 benchmarks · 4 datasets archive 2025-07-28
Benchmarks archive 2025-07-28
No benchmark for this task in the archive.
Libraries
Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.
Datasets archive 2025-07-28
4 datasets whose archive record lists this task, ordered by the archive's paper count.
Subtasks archive 2025-07-28
1 subtask in the archive's task tree.
Most implemented papers archive 2025-07-28
26 shown of 26 papers with code (139 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.
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19 Aug 2020 2 repositories listedThis paper proposes the first known to us open source hardware and software iris recognition system with presentation attack detection (PAD), which can be easily assembled for about 75 USD using Raspberry Pi board and a…
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2 Jul 2020 2 repositories listedAn iris recognition system is vulnerable to presentation attacks, or PAs, where an adversary presents artifacts such as printed eyes, plastic eyes, or cosmetic contact lenses to circumvent the system.
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13 Jul 2019 2 repositories listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)We observe equal error rates of 1.
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7 Jan 2019 2 repositories listedWe propose to use deep learning-based iris segmentation models to extract highly irregular iris texture areas in post-mortem iris images.
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26 Sep 2018 2 repositories listedThis paper proposes the first, known to us, open source presentation attack detection (PAD) solution to distinguish between authentic iris images (possibly wearing clear contact lenses) and irises with textured contact…
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13 Jul 2018 2 repositories listedOne important point is that all applications of BSIF in iris recognition have used the original BSIF filters, which were trained on image patches extracted from natural images.
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14 Apr 2025 1 repository listedConsidering all, in this paper, we benchmark blurring, noising, downsampling, rubber sheet model, and iris style transfer to obfuscate user identity, and compare their impact on image quality, privacy, utility, and risk…
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6 Mar 2025 1 repository listedIris texture is widely regarded as a gold standard biometric modality for authentication and identification.
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24 Aug 2024 1 repository listedIn the last few years, face morphing has been shown to be a complex challenge for Face Recognition Systems (FRS).
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28 Jun 2024 1 repository listedIn this work, we propose a generative iris prior embedded Transformer model (Gformer), in which we build a hierarchical encoder-decoder network employing Transformer block and generative iris prior.
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19 Dec 2023 1 repository listedSynthesis of same-identity biometric iris images, both for existing and non-existing identities while preserving the identity across a wide range of pupil sizes, is complex due to intricate iris muscle constriction…
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7 Dec 2023 1 repository listedThis paper makes a novel contribution to facilitate progress in post-mortem iris recognition by offering a conditional StyleGAN-based iris synthesis model, trained on the largest-available dataset of post-mortem iris…
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24 Dec 2022 1 repository listedThe results indicate that our data augmentation method can improve segmentation accuracy up to 15% for images with high pupil dilation, which creates a more reliable iris recognition pipeline, even under extreme…
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18 Jul 2022 1 repository listedNonlinear iris texture deformations due to pupil size variations are one of the main factors responsible for within-class variance of genuine comparison scores in iris recognition.
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3 Jan 2022 1 repository listedIris recognition requires an adequate level of the iris texture being visible to perform a reliable matching.
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9 Dec 2021 1 repository listedFurther, we have introduced a new dataset, called KartalOl, to better evaluate detectors in iris recognition scenarios.
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1 Dec 2021 1 repository listedIn this paper, we present an end-to-end deep learning-based method for postmortem iris segmentation and recognition with a special visualization technique intended to support forensic human examiners in their efforts.
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29 Jun 2021 1 repository listedTo accommodate users at different distances, it is necessary to control focus quickly and accurately.
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31 Jul 2020 1 repository listedThat is, we show how to transform templates into realistic looking iris images that are also deemed as the same iris by the corresponding recognition system.
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20 Feb 2020 1 repository listedFeatures are extracted from each convolutional layer and the classification accuracy achieved by a Support Vector Machine is measured on a dataset that is disjoint from the samples used in training of the ResNet-50…
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8 Sep 2019 1 repository listedTo attain accurate and efficient FCN models, we propose a three-step SW/HW co-design methodology consisting of FCN architectural exploration, precision quantization, and hardware acceleration.
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22 Jul 2019 1 repository listedIris recognition has been an active research area during last few decades, because of its wide applications in security, from airports to homeland security border control.
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1 May 2019 1 repository listedThis paper explores the use of a Binary Statistical Features (BSIF) algorithm for classifying gender from iris texture images captured with NIR sensors.
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4 Jan 2019 1 repository listedThis paper offers three new, open-source, deep learning-based iris segmentation methods, and the methodology how to use irregular segmentation masks in a conventional Gabor-wavelet-based iris recognition.
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25 Nov 2018 1 repository listedThe adoption of large-scale iris recognition systems around the world has brought to light the importance of detecting presentation attack images (textured contact lenses and printouts).
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4 May 2018 1 repository listedRecent research has explored the possibility of automatically deducing information such as gender, age and race of an individual from their biometric data.
Syntology lines on 1 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.
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