49 citations · 217 across the 32 of their papers we have counts for
5 papers · 1 filter
Kitting in the Wild through Online Domain Adaptation
Massimiliano Mancini, Hakan Karaoguz, Elisa Ricci +2
Technological developments call for increasing perception and action capabilities of robots. Among other skills, vision systems that can adapt to any possible change in the working…
Best sources forward: domain generalization through source-specific nets
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo +1
A long standing problem in visual object categorization is the ability of algorithms to generalize across different testing conditions. The problem has been formalized as a covaria…
Adding New Tasks to a Single Network with Weight Transformations using Binary Masks
Massimiliano Mancini, Elisa Ricci, Barbara Caputo +1
Visual recognition algorithms are required today to exhibit adaptive abilities. Given a deep model trained on a specific, given task, it would be highly desirable to be able to ada…
Robust Place Categorization with Deep Domain Generalization
Massimiliano Mancini, Samuel Rota Bulò, Barbara Caputo +1
Traditional place categorization approaches in robot vision assume that training and test images have similar visual appearance. Therefore, any seasonal, illumination and environme…
Boosting Domain Adaptation by Discovering Latent Domains
Massimiliano Mancini, Lorenzo Porzi, Samuel Rota Bulò +2
Current Domain Adaptation (DA) methods based on deep architectures assume that the source samples arise from a single distribution. However, in practice, most datasets can be regar…