47 citations · 110 across the 27 of their papers we have counts for
3 papers · 1 filter
From source to target and back: symmetric bi-directional adaptive GAN
Paolo Russo, Fabio Maria Carlucci, Tatiana Tommasi +1
The effectiveness of generative adversarial approaches in producing images according to a specific style or visual domain has recently opened new directions to solve the unsupervis…
Training Deep Networks without Learning Rates Through Coin Betting
Francesco Orabona, Tatiana Tommasi
Deep learning methods achieve state-of-the-art performance in many application scenarios. Yet, these methods require a significant amount of hyperparameters tuning in order to achi…
Learning Deep Visual Object Models From Noisy Web Data: How to Make it Work
Nizar Massouh, Francesca Babiloni, Tatiana Tommasi +3
Deep networks thrive when trained on large scale data collections. This has given ImageNet a central role in the development of deep architectures for visual object classification.…