Project and Mix: Task-Semantic Prototypes for Few-Shot Image Classification
This framework improves few-shot image classification by intelligently mixing class prototypes from Vision-Language Models (VLMs) like CLIP. It decomposes image prototypes into text-aligned and orthogonal components, applying a targeted mixing strategy to optimize performance across different shot settings.