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20192026
most citedAudio-Visual Biometric Recognition and Presentation Attack Detection: A Comprehensive Survey

41 citations · 94 across the 53 of their papers we have counts for

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cs.CV2026

OpenVeinNet: Robust Open-Set Finger Vein Verification with Dynamic Snake Convolution and Graph Learning

Sushrut Patwardhan, Raghavendra Ramachandra

Finger vein verification is a promising biometric modality for secure authentication because vascular patterns are internal, difficult to observe externally, and relatively resista…

cs.CV2026

A Systematic Failure Analysis of Vision Foundation Models for Open Set Iris Presentation Attack Detection

Rahul Anand, Siddharth Singh, Dileep A D +2

Vision foundation models have demonstrated strong transferability across diverse visual recognition tasks and are increasingly considered for biometric applications. Their suitabil…

cs.CV2026

DCMorph: Face Morphing via Dual-Stream Cross-Attention Diffusion

Tahar Chettaoui, Eduarda Caldeira, Guray Ozgur +3

Advancing face morphing attack techniques is crucial to anticipate evolving threats and develop robust defensive mechanisms for identity verification systems. This work introduces…

cs.CV2026

R-FLoRA: Residual-Statistic-Gated Low-Rank Adaptation for Single-Image Face Morphing Attack Detection

Raghavendra Ramachandra

Face morphing attacks pose a substantial risk to the reliability of face recognition systems used in passport issuance, border control, and digital identity verification. Detecting…

cs.CV2026

The Fourth Challenge on Image Super-Resolution (4) at NTIRE 2026: Benchmark Results and Method Overview

Zheng Chen, Kai Liu, Jingkai Wang +150

This paper presents the NTIRE 2026 image super-resolution (4) challenge, one of the associated competitions of the NTIRE 2026 Workshop at CVPR 2026. The challenge aims to r…

cs.CV2025

SpectraIrisPAD: Leveraging Vision Foundation Models for Spectrally Conditioned Multispectral Iris Presentation Attack Detection

Raghavendra Ramachandra, Sushma Venkatesh

Iris recognition is widely recognized as one of the most accurate biometric modalities. However, its growing deployment in real-world applications raises significant concerns regar…