28 citations · 39 across the 11 of their papers we have counts for
16 papers
Learning with Style: Continual Semantic Segmentation Across Tasks and Domains
Marco Toldo, Umberto Michieli, Pietro Zanuttigh
Deep learning models dealing with image understanding in real-world settings must be able to adapt to a wide variety of tasks across different domains. Domain adaptation and class…
Learning Across Domains and Devices: Style-Driven Source-Free Domain Adaptation in Clustered Federated Learning
Donald Shenaj, Eros Fanì, Marco Toldo +6
Federated Learning (FL) has recently emerged as a possible way to tackle the domain shift in real-world Semantic Segmentation (SS) without compromising the private nature of the co…
A Low Memory Footprint Quantized Neural Network for Depth Completion of Very Sparse Time-of-Flight Depth Maps
Xiaowen Jiang, Valerio Cambareri, Gianluca Agresti +4
Sparse active illumination enables precise time-of-flight depth sensing as it maximizes signal-to-noise ratio for low power budgets. However, depth completion is required to produc…
SELMA: SEmantic Large-scale Multimodal Acquisitions in Variable Weather, Daytime and Viewpoints
Paolo Testolina, Francesco Barbato, Umberto Michieli +3
Accurate scene understanding from multiple sensors mounted on cars is a key requirement for autonomous driving systems. Nowadays, this task is mainly performed through data-hungry…
End-to-end Learning for Joint Depth and Image Reconstruction from Diffracted Rotation
Mazen Mel, Muhammad Siddiqui, Pietro Zanuttigh
Monocular depth estimation is still an open challenge due to the ill-posed nature of the problem at hand. Deep learning based techniques have been extensively studied and proved ca…
RECALL: Replay-based Continual Learning in Semantic Segmentation
Andrea Maracani, Umberto Michieli, Marco Toldo +1
Deep networks allow to obtain outstanding results in semantic segmentation, however they need to be trained in a single shot with a large amount of data. Continual learning setting…