23 citations · 63 across the 20 of their papers we have counts for
3 papers · 1 filter
Prototype-based Incremental Few-Shot Semantic Segmentation
Fabio Cermelli, Massimiliano Mancini, Yongqin Xian +2
Semantic segmentation models have two fundamental weaknesses: i) they require large training sets with costly pixel-level annotations, and ii) they have a static output space, cons…
Boosting Deep Open World Recognition by Clustering
Dario Fontanel, Fabio Cermelli, Massimiliano Mancini +3
While convolutional neural networks have brought significant advances in robot vision, their ability is often limited to closed world scenarios, where the number of semantic concep…
Modeling the Background for Incremental Learning in Semantic Segmentation
Fabio Cermelli, Massimiliano Mancini, Samuel Rota Bulò +2
Despite their effectiveness in a wide range of tasks, deep architectures suffer from some important limitations. In particular, they are vulnerable to catastrophic forgetting, i.e.…