mlsanityData to 14 Oct 2026

Two-headed eye-segmentation approach for biometric identification

arXiv 2209.15471 ↗First posted 30 Sep 2022cs.CV cs.LGcited by 3

Not on the map. Why?

Abstract (arXiv)

Iris-based identification systems are among the most popular approaches for person identification. Such systems require good-quality segmentation modules that ideally identify the regions for different eye components. This paper introduces the new two-headed architecture, where the eye components and eyelashes are segmented using two separate decoding modules. Moreover, we investigate various training scenarios by adopting different training losses. Thanks to the two-headed approach, we were also able to examine the quality of the model with the convex prior, which enforces the convexity of the segmented shapes. We conducted an extensive evaluation of various learning scenarios on real-life conditions high-resolution near-infrared iris images.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 15 of its 18 references that are in the map. First posted on arXiv 30 Sep 2022.

Builds on

15 of 18 references.

References · 15

  1. 2015U-Net: Convolutional Networks for Biomedical Image Segmentationcited by 19,713
  2. 2014Fully Convolutional Networks for Semantic Segmentationcited by 4,859
  3. 2016DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFscited by 3,241
  4. 2018Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentationcited by 3,223
  5. 2016Pyramid Scene Parsing Networkcited by 2,479
  6. 2017Rethinking Atrous Convolution for Semantic Image Segmentationcited by 2,161
  7. 2019Searching for MobileNetV3cited by 1,994
  8. 2015Multi-Scale Context Aggregation by Dilated Convolutionscited by 1,133
  9. 2017Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentationscited by 620
  10. 2014Semantic Image Segmentation with Deep Convolutional Nets and Fully Connected CRFscited by 554
  11. 2018Learning Pixel-level Semantic Affinity with Image-level Supervision for Weakly Supervised Semantic Segmentationcited by 321
  12. 2020Semi-supervised Medical Image Segmentation through Dual-task Consistencycited by 216
3 more
  1. 2021Unsupervised Semantic Segmentation by Contrasting Object Mask Proposalscited by 190
  2. 2019RITnet: Real-time Semantic Segmentation of the Eye for Gaze Trackingcited by 33
  3. 2020Convex Shape Prior for Deep Neural Convolution Network based Eye Fundus Images Segmentationcited by 10

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2024: 1; 2025: 1; 2026: 1.

3 papers.

  1. 2025Iris Recognition for Infantscited by 2
  2. 2026Lowering the Barrier to IREX Participation: Open-Source Algorithms, Toolkit, and Benchmarking for Iris Recognitioncited by 1
  3. 2024Trustworthy Compression? Impact of AI-based Codecs on Biometrics for Law Enforcementcited by 0