[{"date_published":"2025-06-15T00:00:00Z","citation":{"ieee":"B. Prach and C. Lampert, “Intriguing properties of robust classification,” in <i>2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops</i>, Nashville, TN, United States, 2025, pp. 660–669.","short":"B. Prach, C. Lampert, in:, 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops, IEEE, 2025, pp. 660–669.","ama":"Prach B, Lampert C. Intriguing properties of robust classification. In: <i>2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops</i>. IEEE; 2025:660-669. doi:<a href=\"https://doi.org/10.1109/CVPRW67362.2025.00071\">10.1109/CVPRW67362.2025.00071</a>","ista":"Prach B, Lampert C. 2025. Intriguing properties of robust classification. 2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops. CVPR: Conference on Computer Vision and Pattern Recognition, 660–669.","chicago":"Prach, Bernd, and Christoph Lampert. “Intriguing Properties of Robust Classification.” In <i>2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops</i>, 660–69. IEEE, 2025. <a href=\"https://doi.org/10.1109/CVPRW67362.2025.00071\">https://doi.org/10.1109/CVPRW67362.2025.00071</a>.","apa":"Prach, B., &#38; Lampert, C. (2025). Intriguing properties of robust classification. In <i>2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops</i> (pp. 660–669). Nashville, TN, United States: IEEE. <a href=\"https://doi.org/10.1109/CVPRW67362.2025.00071\">https://doi.org/10.1109/CVPRW67362.2025.00071</a>","mla":"Prach, Bernd, and Christoph Lampert. “Intriguing Properties of Robust Classification.” <i>2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops</i>, IEEE, 2025, pp. 660–69, doi:<a href=\"https://doi.org/10.1109/CVPRW67362.2025.00071\">10.1109/CVPRW67362.2025.00071</a>."},"main_file_link":[{"url":"https://doi.org/10.48550/arXiv.2412.04245","open_access":"1"}],"status":"public","OA_type":"green","doi":"10.1109/CVPRW67362.2025.00071","month":"06","related_material":{"record":[{"relation":"earlier_version","status":"public","id":"18874"}]},"abstract":[{"lang":"eng","text":"Despite extensive research since the community learned about adversarial examples 10 years ago, we still do not know how to train high-accuracy classifiers that are guaranteed to be robust to small perturbations of their inputs. Previous works often argued that this might be because no classifier exists that is robust and accurate at the same time. However, in computer vision this assumption does not match reality where humans are usually accurate and robust on most tasks of interest. We offer an alternative explanation and show that in certain settings robust generalization is only possible with unrealistically large amounts of data. Specifically, we find a setting where a robust classifier exists, it is easy to learn an accurate classifier, yet it requires an exponential amount of data to learn a robust classifier. Based on this theoretical result, we evaluate the influence of the amount of training data on datasets such as CIFAR10. Our findings indicate that the the amount of training data is the main factor determining the robust performance. Furthermore we show that that there are low magnitude directions in the data which are useful for non-robust generalization but are not available for robust classifiers. This implies that robust classification is a strictly harder tasks than normal classification, thereby providing an explanation why robust classification requires more data."}],"oa_version":"Preprint","external_id":{"arxiv":["2412.04245"]},"type":"conference","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","date_updated":"2026-10-02T11:15:42Z","fulldoi":"https://doi.org/10.1109/CVPRW67362.2025.00071","publication_status":"published","article_processing_charge":"No","department":[{"_id":"ChLa"}],"_id":"20455","page":"660-669","date_created":"2025-10-12T22:01:26Z","publisher":"IEEE","publication_identifier":{"eissn":["2160-7516"],"issn":["2160-7508"],"isbn":["9798331599942"]},"scopus_import":"1","quality_controlled":"1","title":"Intriguing properties of robust classification","author":[{"first_name":"Bernd","full_name":"Prach, Bernd","id":"2D561D42-C427-11E9-89B4-9C1AE6697425","last_name":"Prach"},{"orcid":"0000-0001-8622-7887","first_name":"Christoph","id":"40C20FD2-F248-11E8-B48F-1D18A9856A87","last_name":"Lampert","full_name":"Lampert, Christoph"}],"publication":"2025 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops","arxiv":1,"day":"15","year":"2025","language":[{"iso":"eng"}],"OA_place":"repository","corr_author":"1","oa":1,"conference":{"start_date":"2025-06-11","end_date":"2025-06-12","location":"Nashville, TN, United States","name":"CVPR: Conference on Computer Vision and Pattern Recognition"}},{"date_created":"2024-10-15T11:20:54Z","_id":"18381","extern":"1","citation":{"chicago":"Bronstein, Alex M., and Michael M. Bronstein. “Not Only Size Matters: Regularized Partial Matching of Nonrigid Shapes.” In <i>2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</i>. IEEE, 2008. <a href=\"https://doi.org/10.1109/cvprw.2008.4563077\">https://doi.org/10.1109/cvprw.2008.4563077</a>.","ama":"Bronstein AM, Bronstein MM. Not only size matters: Regularized partial matching of nonrigid shapes. In: <i>2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</i>. IEEE; 2008. doi:<a href=\"https://doi.org/10.1109/cvprw.2008.4563077\">10.1109/cvprw.2008.4563077</a>","ista":"Bronstein AM, Bronstein MM. 2008. Not only size matters: Regularized partial matching of nonrigid shapes. 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops. CVPR: Conference on Computer Vision and Pattern Recognition.","ieee":"A. M. Bronstein and M. M. Bronstein, “Not only size matters: Regularized partial matching of nonrigid shapes,” in <i>2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</i>, Anchorage, AK, United States, 2008.","short":"A.M. Bronstein, M.M. Bronstein, in:, 2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops, IEEE, 2008.","mla":"Bronstein, Alex M., and Michael M. Bronstein. “Not Only Size Matters: Regularized Partial Matching of Nonrigid Shapes.” <i>2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</i>, IEEE, 2008, doi:<a href=\"https://doi.org/10.1109/cvprw.2008.4563077\">10.1109/cvprw.2008.4563077</a>.","apa":"Bronstein, A. M., &#38; Bronstein, M. M. (2008). Not only size matters: Regularized partial matching of nonrigid shapes. In <i>2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops</i>. Anchorage, AK, United States: IEEE. <a href=\"https://doi.org/10.1109/cvprw.2008.4563077\">https://doi.org/10.1109/cvprw.2008.4563077</a>"},"date_published":"2008-07-01T00:00:00Z","doi":"10.1109/cvprw.2008.4563077","status":"public","scopus_import":"1","abstract":[{"lang":"eng","text":"Partial matching is probably one of the most challenging problems in nonrigid shape analysis. The problem consists of matching similar parts of shapes that are dissimilar on the whole and can assume different forms by undergoing nonrigid deformations. Conceptually, two shapes can be considered partially matching if they have significant similar parts, with the simplest definition of significance being the size of the parts. Thus, partial matching can be defined as a multicriterion optimization problem trying to simultaneously maximize the similarity and the size of these parts. In this paper, we propose a different definition of significance, taking into account the regularity of parts besides their size. The regularity term proposed here is similar to the spirit of the Mumford-Shah functional. Numerical experiments show that the regularized partial matching produces semantically better results compared to the non-regularized one."}],"month":"07","publisher":"IEEE","publication_identifier":{"isbn":["9781424423392"],"issn":["2160-7508"]},"author":[{"id":"58f3726e-7cba-11ef-ad8b-e6e8cb3904e6","last_name":"Bronstein","full_name":"Bronstein, Alexander","first_name":"Alexander","orcid":"0000-0001-9699-8730"},{"first_name":"Michael M.","full_name":"Bronstein, Michael M.","last_name":"Bronstein"}],"type":"conference","quality_controlled":"1","oa_version":"None","title":"Not only size matters: Regularized partial matching of nonrigid shapes","fulldoi":"https://doi.org/10.1109/cvprw.2008.4563077","date_updated":"2024-11-18T10:18:28Z","publication":"2008 IEEE Computer Society Conference on Computer Vision and Pattern Recognition Workshops","publication_status":"published","user_id":"2DF688A6-F248-11E8-B48F-1D18A9856A87","day":"01","language":[{"iso":"eng"}],"year":"2008","conference":{"location":"Anchorage, AK, United States","name":"CVPR: Conference on Computer Vision and Pattern Recognition","end_date":"2008-06-28","start_date":"2008-06-23"},"article_processing_charge":"No"}]