Incremental Few-Shot Semantic Segmentation via Embedding Adaptive-Update and Hyper-class Representation

no code implementations • 26 Jul 2022 • Guangchen Shi, Yirui Wu, Jun Liu, Shaohua Wan, Wenhai Wang, Tong Lu

Second, to resist overfitting issues caused by few training samples, a hyper-class embedding is learned by clustering all category embeddings for initialization and aligned with category embedding of the new class for enhancement, where learned knowledge assists to learn new knowledge, thus alleviating performance dependence on training data scale.

Few-Shot Semantic Segmentation Semantic Segmentation