117 citations · 177 across the 11 of their papers we have counts for
3 papers · 1 filter
Stop Throwing Away Discriminators! Re-using Adversaries for Test-Time Training
Gabriele Valvano, Andrea Leo, Sotirios A. Tsaftaris
Thanks to their ability to learn data distributions without requiring paired data, Generative Adversarial Networks (GANs) have become an integral part of many computer vision metho…
Self-supervised Multi-scale Consistency for Weakly Supervised Segmentation Learning
Gabriele Valvano, Andrea Leo, Sotirios A. Tsaftaris
Collecting large-scale medical datasets with fine-grained annotations is time-consuming and requires experts. For this reason, weakly supervised learning aims at optimising machine…
Re-using Adversarial Mask Discriminators for Test-time Training under Distribution Shifts
Gabriele Valvano, Andrea Leo, Sotirios A. Tsaftaris
Thanks to their ability to learn flexible data-driven losses, Generative Adversarial Networks (GANs) are an integral part of many semi- and weakly-supervised methods for medical im…