Jinyi Chang

TOWARDS PRIVACY-PRESERVING FINE-GRAINED VISUAL CLASSIFICATION VIA HIERARCHICAL LEARNING FROM LABEL PROPORTIONS

In recent years, Fine-Grained Visual Classification (FGVC) has achieved impressive recognition accuracy, despite minimal inter-class variations. However, existing methods heavily rely on instance-level labels, making them impractical in privacy-sensitive scenarios such as medical image analysis. Thi…