{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/steex-steering-counterfactual-explanations","title":"STEEX: Steering Counterfactual Explanations with Semantics","arxiv_id":"2111.09094","date":"2021-11-17","proceeding":null,"authors":["Paul Jacob","Éloi Zablocki","Hédi Ben-Younes","Mickaël Chen","Patrick Pérez","Matthieu Cord"],"abstract":"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 which preserve the overall scene structure. Furthermore, we introduce the concept of \"region-targeted counterfactual explanations\", and a corresponding framework, where users can guide the generation of counterfactuals by specifying a set of semantic regions of the query image the explanation must be about. Extensive experiments are conducted on challenging datasets including high-quality portraits (CelebAMask-HQ) and driving scenes (BDD100k). Code is available at https://github.com/valeoai/STEEX","url_abs":"https://arxiv.org/abs/2111.09094v3","url_pdf":"https://arxiv.org/pdf/2111.09094v3.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"steex-steering-counterfactual-explanations","repo_url":"https://github.com/valeoai/steex","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"pytorch","reach":null},{"paper_slug":"steex-steering-counterfactual-explanations","repo_url":"https://github.com/sobieskibj/rcsb","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"counterfactual-explanation","task_name":"Counterfactual Explanation"},{"task_slug":null,"task_name":"counterfactual"}],"methods":[{"method_slug":"counterfactuals","method_name":"Counterfactuals"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2111.09094","mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}