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 […]
Lifelong Fine-grained Image Retrieval
Fine-grained image retrieval has been extensively explored in a zero-shot manner. A deep model is trained on the seen part and then […]
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 […]
Temporal Self-Ensembling Teacher for Semi-Supervised Object Detection
This paper focuses on the semi-supervised object detection (SSOD) which makes good use of unlabeled data to boost performance. We face the […]