Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations
Continual Semantic Segmentation via Repulsion-Attraction of Sparse and Disentangled Latent Representations
Deep neural networks suffer from the major limitation of catastrophic forgetting old tasks when learning new ones. In this paper we focus on class incremental continual learning in semantic segmentation, where new categories are made available over time while previous training data is not retained. The proposed continual learning scheme …