3 papers
cs.CR2026
SpooFL: Spoofing Federated Learning
Isaac Baglin, Xiatian Zhu, Simon Hadfield
Traditional defenses against Deep Leakage (DL) attacks in Federated Learning (FL) primarily focus on obfuscation, introducing noise, transformations or encryption to degrade an att…
cs.CV2026
Deep Leakage with Generative Flow Matching Denoiser
Isaac Baglin, Xiatian Zhu, Simon Hadfield
Federated Learning (FL) has emerged as a powerful paradigm for decentralized model training, yet it remains vulnerable to deep leakage (DL) attacks that reconstruct private client…
cs.CV2025
EvtSlowTV -- A Large and Diverse Dataset for Event-Based Depth Estimation
Sadiq Layi Macaulay, Nimet Kaygusuz, Simon Hadfield
Event cameras, with their high dynamic range (HDR) and low latency, offer a promising alternative for robust depth estimation in challenging environments. However, many event-based…