Few-Shot Class-Incremental Learning for Classification and Object Detection: A Survey
Deep Learning for Cross-Domain Few-Shot Visual Recognition: A Survey
While deep learning excels in computer vision tasks with abundant labeled data, its performance diminishes significantly in scenarios with limited labeled samples. […]
Rethinking Few-Shot Class-Incremental Learning with Open-Set Hypothesis in Hyperbolic Geometry
By training first with a large base dataset, FewShot Class-Incremental Learning (FSCIL) aims at continually learning a sequence of few-shot learning tasks […]
Uncertainty-Guided Semi-Supervised Few-Shot Class-Incremental Learning With Knowledge Distillation
Class-Incremental Learning (CIL) aims at incrementally learning novel classes without forgetting old ones. This capability becomes more challenging when novel tasks contain […]