Leveraging Diffusion Models for Semantic Image Augmentation to Improve Deep Learning Model Generalization

Leveraging the capabilities of diffusion models, this paper proposes a technique to generate diverse and photorealistic images based on textual inputs, enabling effective data augmentation to improve the out-of-domain generalization of deep learning models.