AGVBench: A Reliability-Oriented Benchmark of Data Augmentation for Vein Recognition

Researchers published AGVBench, a benchmark evaluating 30 data augmentation strategies for vein recognition across 5 datasets and 7 architectures. The study reveals inconsistencies between accuracy and adversarial security, and highlights dataset-specific effectiveness variations. This work aims to guide the design of reliable vein recognition systems.