Dataset Groups Activity Stream Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers A benchmark for assessing the performance of fairness mitigation methods in computer vision. BibTex: @dataset{Dominik_Zietlow_and_Michael_Lohaus_and_Guha_Balakrishnan_and_Matth¨aus_Kleindessner_and_Francesco_Locatello_and_Bernhard_Sch¨olkopf_and_Chris_Russell_2025, abstract = {A benchmark for assessing the performance of fairness mitigation methods in computer vision.}, author = {Dominik Zietlow and Michael Lohaus and Guha Balakrishnan and Matth¨aus Kleindessner and Francesco Locatello and Bernhard Sch¨olkopf and Chris Russell}, doi = {10.57702/o9jwzgnm}, institution = {No Organization}, keyword = {'computer vision', 'deep learning', 'fairness mitigation'}, month = {jan}, publisher = {TIB}, title = {Leveling down in computer vision: Pareto inefficiencies in fair deep classifiers}, url = {https://service.tib.eu/ldmservice/dataset/leveling-down-in-computer-vision--pareto-inef-ciencies-in-fair-deep-classi-ers}, year = {2025} }
