STEEX: Steering Counterfactual Explanations with Semantics. (arXiv:2111.09094v3 [cs.CV] UPDATED)

As deep learning models are increasingly used in safety-critical
applications, explainability and trustworthiness become major concerns. For
simple images, such as low-resolution face portraits, synthesizing visual
counterfactual explanations has recently been proposed as a way to uncover the
decision mechanisms of a trained classification model. In this work, we address
the problem of producing counterfactual explanations for high-quality images
and complex scenes. Leveraging recent semantic-to-image models, we propose a
new generative counterfactual explanation framework that produces plausible and
sparse modifications …

arxiv cv semantics