32 citations · 66 across the 9 of their papers we have counts for
9 papers
Model Debiasing by Learnable Data Augmentation
Pietro Morerio, Ruggero Ragonesi, Vittorio Murino
Deep Neural Networks are well known for efficiently fitting training data, yet experiencing poor generalization capabilities whenever some kind of bias dominates over the actual ta…
Learnable Data Augmentation for One-Shot Unsupervised Domain Adaptation
Julio Ivan Davila Carrazco, Pietro Morerio, Alessio Del Bue +1
This paper presents a classification framework based on learnable data augmentation to tackle the One-Shot Unsupervised Domain Adaptation (OS-UDA) problem. OS-UDA is the most chall…
Leveraging Next-Active Objects for Context-Aware Anticipation in Egocentric Videos
Sanket Thakur, Cigdem Beyan, Pietro Morerio +2
Objects are crucial for understanding human-object interactions. By identifying the relevant objects, one can also predict potential future interactions or actions that may occur w…
Continual Source-Free Unsupervised Domain Adaptation
Waqar Ahmed, Pietro Morerio, Vittorio Murino
Existing Source-free Unsupervised Domain Adaptation (SUDA) approaches inherently exhibit catastrophic forgetting. Typically, models trained on a labeled source domain and adapted t…
Unsupervised Domain Adaptation for Video Transformers in Action Recognition
Victor G. Turrisi da Costa, Giacomo Zara, Paolo Rota +4
Over the last few years, Unsupervised Domain Adaptation (UDA) techniques have acquired remarkable importance and popularity in computer vision. However, when compared to the extens…
Modeling Retinal Ganglion Cell Population Activity with Restricted Boltzmann Machines
Matteo Zanotto, Riccardo Volpi, Alessandro Maccione +3
The retina is a complex nervous system which encodes visual stimuli before higher order processing occurs in the visual cortex. In this study we evaluated whether information about…