{"url":"/dataset/ufpr-eyeglasses","name":"UFPR-Eyeglasses","full_name":null,"description_markdown":"The UFPR-Eyeglasses dataset has 1,135 images of both eyes (2,270 cropped images of each eye) from 83 subjects (166 classes). The dataset is used to evaluate the effect of the occlusion caused by eyeglasses in periocular recognition.\r\n\r\nSource: [Unconstrained Periocular Recognition: Using Generative Deep Learning Frameworks for Attribute Normalization](https://arxiv.org/abs/2002.03985)","description_withheld":null,"homepage":"https://web.inf.ufpr.br/vri/databases/ufpr-eyeglasses/","introduced_date":"2020-02-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/unconstrained-periocular-recognition-using","title":"Unconstrained Periocular Recognition: Using Generative Deep Learning Frameworks for Attribute Normalization","first_author":"Luiz A. Zanlorensi","url":null},"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[],"languages":[],"variants":["UFPR-Eyeglasses"],"data_loaders":[],"num_papers_in_archive":2,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"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."}