{"url":"/dataset/flickrlogos-32","name":"FlickrLogos-32","full_name":null,"description_markdown":"Object detection benchmark for logo detection.\r\n\r\nImages are natural scenes. Each image contains multiple objects, and each image has a total of 1 logo. Logo detection & classification labels are provided.","description_withheld":null,"homepage":"https://www.uni-augsburg.de/en/fakultaet/fai/informatik/prof/mmc/research/datensatze/flickrlogos/","introduced_date":"2011-04-17","introduced_date_note":null,"introduced_by":{"paper":"/paper/scalable-logo-recognition-in-real-world","title":"Scalable logo recognition in real-world images","first_author":"Stefan Romberg","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Image Classification","url":"/task/image-classification","datasets_with_task":"/datasets/task/image-classification"},{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"Object Detection","url":"/task/object-detection","datasets_with_task":"/datasets/task/object-detection"},{"name":"Traffic Sign Recognition","url":"/task/traffic-sign-recognition","datasets_with_task":"/datasets/task/traffic-sign-recognition"}],"languages":[],"variants":["FlickrLogos-32"],"data_loaders":[],"num_papers_in_archive":26,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/image-classification-on-flickrlogos-32","task":"Image Classification","dataset_variant":"FlickrLogos-32","rows":3,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"TC-VII (with outside data)","paper":"/paper/deep-learning-for-logo-recognition","metrics":{"Accuracy":"96.0"},"code_links":[]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/object-detection-on-flickrlogos-32","task":"Object Detection","dataset_variant":"FlickrLogos-32","rows":3,"metrics":["MAP"],"first_row_in_archive_order":{"model":"Logo-Yolo","paper":"/paper/logodet-3k-a-large-scale-image-dataset-for","metrics":{"MAP":"76.11"},"code_links":[{"title":"Wangjing1551/LogoDet-3K-Dataset","url":"https://github.com/Wangjing1551/LogoDet-3K-Dataset"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/traffic-sign-recognition-on-flickrlogos-32","task":"Traffic Sign Recognition","dataset_variant":"FlickrLogos-32","rows":1,"metrics":["Accuracy"],"first_row_in_archive_order":{"model":"Sill-Net","paper":"/paper/sill-net-feature-augmentation-with-separated","metrics":{"Accuracy":"95.80"},"code_links":[{"title":"lanfenghuanyu/Sill-Net","url":"https://github.com/lanfenghuanyu/Sill-Net"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/sill-net-feature-augmentation-with-separated","title":"Sill-Net: Feature Augmentation with Separated Illumination Representation","date":"2021-02-06","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/logodet-3k-a-large-scale-image-dataset-for","title":"LogoDet-3K: A Large-Scale Image Dataset for Logo Detection","date":"2020-08-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/deep-learning-for-logo-recognition","title":"Deep Learning for Logo Recognition","date":"2017-01-10","rows_on_this_dataset":2,"code_links":0,"syntology":null},{"paper":"/paper/deeplogo-hitting-logo-recognition-with-the","title":"DeepLogo: Hitting Logo Recognition with the Deep Neural Network Hammer","date":"2015-10-07","rows_on_this_dataset":3,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}