Global-to-Local Visual Conditioning for Image Captioning with a Frozen Vision–Language Model
This study investigates an input-level visual conditioning approach for image captioning using a frozen ResNet-50 image encoder and a frozen Phi-3 Mini language model, providing an empirical analysis of global and local visual conditioning for parameter-efficient caption generation with frozen pretrained components.