3 papers
cs.CV2026
Federated Medical Image Classification under Class and Domain Imbalance exploiting Synthetic Sample Generation
Martina Pavan, Matteo Caligiuri, Francesco Barbato +1
Exploiting deep learning in medical imaging faces critical challenges, including strict privacy constraints, heterogeneous imaging devices with varying acquisition properties, and…
cs.CV2025
From Open-Vocabulary to Vocabulary-Free Semantic Segmentation
Klara Reichard, Giulia Rizzoli, Stefano Gasperini +4
Open-vocabulary semantic segmentation enables models to identify novel object categories beyond their training data. While this flexibility represents a significant advancement, cu…
cs.CV2024
Learning from the Web: Language Drives Weakly-Supervised Incremental Learning for Semantic Segmentation
Chang Liu, Giulia Rizzoli, Pietro Zanuttigh +2
Current weakly-supervised incremental learning for semantic segmentation (WILSS) approaches only consider replacing pixel-level annotations with image-level labels, while the train…