Explaining in Diffusion: Explaining a Classifier with Diffusion Semantics

https://explain-in-diffusion.github.io Figure 1. DiffEx explains the decisions of domain-specific classifiers by identifying the most influential semantics affecting their predictions. Classifier scores for each example are displayed in the top-left corner, demonstrating how classifier predictions change in response to the manipulation of different semantics (original images are shown with red borders). Our approach is capable of explaining classifiers that concentrate on individual concepts such as faces or animals (top row) as well as those that manage complex scenes involving multiple objects, such as a formal/casual fit in a fashion context (bottom row).