Prompt-driven Zero-shot Domain Adaptation

Prompt-driven Zero-shot Domain Adaptation is an advanced method in the field of computer vision that aims to leverage a single source domain dataset and natural language descriptions of the target domain to achieve rapid adaptation to unseen target domains. This approach constructs a powerful prompting mechanism, enabling the model to effectively transfer knowledge from the source domain without requiring images from the target domain, thereby enhancing cross-domain task performance. Its application value lies in significantly reducing the annotation costs for cross-domain visual tasks, improving the model's generalization ability, and increasing deployment efficiency.