CVPR 2023 - CRAFT: Concept Recursive Activation FacTorization for Explainability

In this episode we discuss CRAFT: Concept Recursive Activation FacTorization for Explainability by Thomas Fel, Agustin Picard, Louis Bethune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre. The paper introduces a new approach called CRAFT to identify "what" and "where" a model looks at in an image. The approach generates concept-based explanations and introduces new ingredients to the automatic concept extraction literature. The proposed concept importance estimation technique is more faithful to the model than previous methods and the usefulness of the approach is demonstrated in both human and computer vision experiments. The code for CRAFT is freely available on GitHub.