Towards Robust Iris Recognition Through Occlusion Identification and Conditional Diffusion-Based Reconstruction
Iris recognition is a reliable biometric approach that identifies individuals using the distinctive and stable texture of the iris. However, recognition performance can degrade when discriminative iris texture is partially occluded by eyelids, eyelashes, specular reflections, or other acquisition artifacts. Existing approaches often perform recognition directly on degraded samples or rely only on the remaining visible iris region, which may be inadequate when substantial texture is corrupted. To address this limitation, we propose an occlusion-aware iris recognition framework with three sequen
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Paper → model → repo connections mined from source citations (Tier-1 exact match).
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Every edge carries a method, confidence, and the source snippet that justified it — so bad links are debuggable.
- FuzzySimilar title/name (fuzzy) · 59%stabilityai/stable-diffusion-xl-base-1.0 →
“Fuzzy title match (0.73): “Towards Robust Iris Recognition Through Occlusion Identifica” ≈ “stabilityai/stable-diffusion-xl-base-1.0””
- FuzzySimilar title/name (fuzzy) · 59%CompVis/stable-diffusion-v1-4 →
“Fuzzy title match (0.73): “Towards Robust Iris Recognition Through Occlusion Identifica” ≈ “CompVis/stable-diffusion-v1-4””
- FuzzySimilar title/name (fuzzy) · 59%stabilityai/stable-diffusion-3.5-large →
“Fuzzy title match (0.73): “Towards Robust Iris Recognition Through Occlusion Identifica” ≈ “stabilityai/stable-diffusion-3.5-large””
- LinkedLinked via arxiv author · 85%Kamrul Hasan →
“Towards Robust Iris Recognition Through Occlusion Identification and Conditional Diffusion-Based Reconstruction”
- LinkedLinked via arxiv author · 85%Mylene C. Q. Farias →
“Towards Robust Iris Recognition Through Occlusion Identification and Conditional Diffusion-Based Reconstruction”
- LinkedLinked via arxiv author · 85%Oleg V. Komogortsev →
“Towards Robust Iris Recognition Through Occlusion Identification and Conditional Diffusion-Based Reconstruction”