Grounding Stylistic Domain Generalization with Quantitative Domain Shift
Measures and Synthetic Scene Images
Grounding Stylistic Domain Generalization with Quantitative Domain Shift
Measures and Synthetic Scene Images
Domain Generalization (DG) is a challenging task in machine learning that requires a coherent ability to comprehend shifts across various domains through extraction of domain-invariant features. DG performance is typically evaluated by performing image classification in domains of various image styles. However, current methodology lacks quantitative understanding about shifts in …