{"url":"/dataset/lfwa","name":"LFWA","full_name":null,"description_markdown":"LFWA is a popular unconstrained facial attribute dataset, which consists of 13,143 facial images of 5,749 identities. Each facial image has 40 attribute annotations.\r\n\r\nImage Source: [https://arxiv.org/pdf/1604.07360.pdf](https://arxiv.org/pdf/1604.07360.pdf)","description_withheld":null,"homepage":"https://mmlab.ie.cuhk.edu.hk/projects/CelebA.html","introduced_date":"2014-11-28","introduced_date_note":null,"introduced_by":{"paper":"/paper/deep-learning-face-attributes-in-the-wild","title":"Deep Learning Face Attributes in the Wild","first_author":"Ziwei Liu","url":null},"license":null,"modalities":[],"tasks":[{"name":"Facial Attribute Classification","url":"/task/facial-attribute-classification","datasets_with_task":"/datasets/task/facial-attribute-classification"}],"languages":[],"variants":["LFWA"],"data_loaders":[],"num_papers_in_archive":63,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/facial-attribute-classification-on-lfwa","task":"Facial Attribute Classification","dataset_variant":"LFWA","rows":7,"metrics":["Error Rate"],"first_row_in_archive_order":{"model":"Label2Label","paper":"/paper/label2label-a-language-modeling-framework-for","metrics":{"Error Rate":"12.49"},"code_links":[{"title":"li-wanhua/label2label","url":"https://github.com/li-wanhua/label2label"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/label2label-a-language-modeling-framework-for","title":"Label2Label: A Language Modeling Framework for Multi-Attribute Learning","date":"2022-07-18","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":5,"samples_ran":2,"samples_unverified":3,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/learning-spatial-semantic-relationship-for","title":"Learning Spatial-Semantic Relationship for Facial Attribute Recognition With Limited Labeled Data","date":"2021-06-19","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/heterogeneous-face-attribute-estimation-a","title":"Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach","date":"2017-06-03","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/improving-facial-attribute-prediction-using","title":"Improving Facial Attribute Prediction using Semantic Segmentation","date":"2017-04-27","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/attributes-for-improved-attributes-a-multi","title":"Attributes for Improved Attributes: A Multi-Task Network for Attribute Classification","date":"2016-04-25","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/deep-learning-face-attributes-in-the-wild","title":"Deep Learning Face Attributes in the Wild","date":"2014-11-28","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":5,"samples_ran":3,"samples_unverified":2,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/panda-pose-aligned-networks-for-deep","title":"PANDA: Pose Aligned Networks for Deep Attribute Modeling","date":"2013-11-21","rows_on_this_dataset":1,"code_links":1,"syntology":null}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":2,"samples_harvested":10,"samples_ran":5,"samples_unverified":5,"pointer_only_for_licence":10,"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."}