Gradient-Guided Exploration of Generative Model's Latent Space for Controlled Iris Image Augmentations

ArXi:2511.09749v2 Announce Type: replace-cross Developing reliable iris recognition and presentation attack detection methods requires diverse datasets that capture realistic variations in iris features and a wide spectrum of anomalies. Because of the rich texture of iris images, which spans a wide range of spatial frequencies, synthesizing same-identity iris images while controlling specific attributes remains challenging. In this work, we