Photo To Rest Generalization

Photo to Rest Generalization is a specific case of Single Source Domain Generalization (SSDG) tasks, focusing on training with easily collected real photos and evaluating on other diverse styles of domains such as artworks, cartoons, and sketches. The goal of this task is to ensure that the model can effectively generalize to unseen image styles after being trained on only a single domain of real photos, thereby enhancing the robustness and adaptability of the model. Due to the compatibility of the real photo domain with ImageNet pre-trained networks, this task has become an important approach for assessing and improving the cross-domain generalization capabilities of computer vision models.