A Generalized Few-Shot Object Detection Method via Extraction of Base-Novel Commonality With Memory Distillation of Category Prototypes

Generalized few-shot object detection aims to improve detection accuracy for novel classes while maintaining high performance on base classes. Traditional fine-tuning approaches often blur feature boundaries, leading to misclassification of novel samples as base classes or background. Additionally,...

Ausführliche Beschreibung