Class Similarity Transition: Decoupling Class Similarities and Imbalance from Generalized Few-shot Segmentation

arXiv:2404.05111v1 Announce Type: new
Abstract: In Generalized Few-shot Segmentation (GFSS), a model is trained with a large corpus of base class samples and then adapted on limited samples of novel classes. This paper focuses on the relevance between base and novel classes, and improves GFSS in two aspects: 1) mining the similarity between base and novel classes to promote the learning of novel classes, and 2) mitigating the class imbalance issue caused by the volume difference between the support set …

arxiv class cs.cv few-shot generalized segmentation transition type