{"url":"/dataset/ijb-c","name":"IJB-C","full_name":"IARPA Janus Benchmark-C","description_markdown":"The **IJB-C** dataset is a video-based face recognition dataset. It is an extension of the IJB-A dataset with about 138,000 face images, 11,000 face videos, and 10,000 non-face images.\r\n\r\nSource: [Pushing the Limits of Unconstrained Face Detection:a Challenge Dataset and Baseline Results](https://arxiv.org/abs/1804.10275)\r\nImage Source: [https://noblis.org/wp-content/uploads/2018/03/icb2018.pdf](https://noblis.org/wp-content/uploads/2018/03/icb2018.pdf)","description_withheld":null,"homepage":"https://www.nist.gov/programs-projects/face-challenges","introduced_date":"2018-01-01","introduced_date_note":null,"introduced_by":{"paper":null,"title":"IARPA Janus Benchmark - C: Face Dataset and Protocol","first_author":null,"url":"https://doi.org/10.1109/ICB2018.2018.00033"},"license":{"name":"Custom (research-only, attribution)","url":"https://nigos.nist.gov/datasets/ijbc/request"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Face Verification","url":"/task/face-verification","datasets_with_task":"/datasets/task/face-verification"},{"name":"Quantization","url":"/task/quantization","datasets_with_task":"/datasets/task/quantization"},{"name":"Lightweight Face Recognition","url":"/task/lightweight-face-recognition","datasets_with_task":"/datasets/task/lightweight-face-recognition"}],"languages":[],"variants":["IJB-C"],"data_loaders":[],"num_papers_in_archive":246,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/face-verification-on-ijb-c","task":"Face Verification","dataset_variant":"IJB-C","rows":26,"metrics":["TAR @ FAR=1e-6","TAR @ FAR=1e-5","TAR @ FAR=1e-4","TAR @ FAR=1e-3","TAR @ FAR=1e-2","training dataset","model","Rank-1","Rank-5"],"first_row_in_archive_order":{"model":"HeadSharing: SH-KD","paper":"/paper/it-s-all-in-the-head-representation-knowledge","metrics":{"TAR @ FAR=1e-4":"95.64%","TAR @ FAR=1e-5":"93.73%","TAR @ FAR=1e-6":"90.24%","model":"MobileFaceNet","training dataset":"MS1M V3"},"code_links":[{"title":"alibaba-miil/headsharingkd","url":"https://github.com/alibaba-miil/headsharingkd"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/lightweight-face-recognition-on-ijb-c","task":"Lightweight Face Recognition","dataset_variant":"IJB-C","rows":3,"metrics":["TAR @ FAR=0.01","MFLOPs","MParams"],"first_row_in_archive_order":{"model":"EdgeFace - S (g=0.5)","paper":"/paper/edgeface-efficient-face-recognition-model-for","metrics":{"MFLOPs":"306.11","MParams":"3.65","TAR @ FAR=0.01":"0.9563"},"code_links":[{"title":"otroshi/edgeface","url":"https://github.com/otroshi/edgeface"},{"title":"anjith2006/bob.paper.tbiom2023_edgeface","url":"https://github.com/anjith2006/bob.paper.tbiom2023_edgeface"},{"title":"bob/bob.paper.tbiom2023_edgeface","url":"https://gitlab.idiap.ch/bob/bob.paper.tbiom2023_edgeface"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/quantization-on-ijb-c","task":"Quantization","dataset_variant":"IJB-C","rows":1,"metrics":["TAR @ FAR=1e-4"],"first_row_in_archive_order":{"model":"","paper":"/paper/quantface-towards-lightweight-face","metrics":{"TAR @ FAR=1e-4":"96.38"},"code_links":[{"title":"fdbtrs/QuantFace","url":"https://github.com/fdbtrs/QuantFace"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/edgeface-efficient-face-recognition-model-for","title":"EdgeFace: Efficient Face Recognition Model for Edge Devices","date":"2023-07-04","rows_on_this_dataset":2,"code_links":3,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/cluster-and-aggregate-face-recognition-with","title":"Cluster and Aggregate: Face Recognition with Large Probe Set","date":"2022-10-19","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":9,"samples_ran":7,"samples_unverified":2,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/controllable-and-guided-face-synthesis-for","title":"Controllable and Guided Face Synthesis for Unconstrained Face Recognition","date":"2022-07-20","rows_on_this_dataset":1,"code_links":3,"syntology":null},{"paper":"/paper/quantface-towards-lightweight-face","title":"QuantFace: Towards Lightweight Face Recognition by Synthetic Data Low-bit Quantization","date":"2022-06-21","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/adaface-quality-adaptive-margin-for-face","title":"AdaFace: Quality Adaptive Margin for Face Recognition","date":"2022-04-03","rows_on_this_dataset":3,"code_links":9,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":22,"samples_ran":17,"samples_unverified":5,"pointer_only_for_licence":11,"claim":"Per-sample execution on synthesized fixtures; 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not a correctness claim."}},{"paper":"/paper/webface260m-a-benchmark-unveiling-the-power","title":"WebFace260M: A Benchmark Unveiling the Power of Million-Scale Deep Face Recognition","date":"2021-03-06","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/curricularface-adaptive-curriculum-learning","title":"CurricularFace: Adaptive Curriculum Learning Loss for Deep Face Recognition","date":"2020-04-01","rows_on_this_dataset":1,"code_links":2,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":13,"samples_ran":10,"samples_unverified":3,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/circle-loss-a-unified-perspective-of-pair","title":"Circle Loss: A Unified Perspective of Pair Similarity Optimization","date":"2020-02-25","rows_on_this_dataset":1,"code_links":16,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":2,"samples_ran":2,"samples_unverified":0,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/probabilistic-face-embeddings","title":"Probabilistic Face Embeddings","date":"2019-04-21","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":1,"samples_ran":1,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/look-across-elapse-disentangled","title":"Look Across Elapse: Disentangled Representation Learning and Photorealistic Cross-Age Face Synthesis for Age-Invariant Face Recognition","date":"2018-09-02","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":6,"samples_ran":0,"samples_unverified":6,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/multicolumn-networks-for-face-recognition","title":"Multicolumn Networks for Face Recognition","date":"2018-07-24","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":4,"samples_ran":0,"samples_unverified":4,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/arcface-additive-angular-margin-loss-for-deep","title":"ArcFace: Additive Angular Margin Loss for Deep Face Recognition","date":"2018-01-23","rows_on_this_dataset":1,"code_links":100,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":21,"samples_ran":16,"samples_unverified":5,"pointer_only_for_licence":14,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/vggface2-a-dataset-for-recognising-faces","title":"VGGFace2: A dataset for recognising faces across pose and age","date":"2017-10-23","rows_on_this_dataset":1,"code_links":24,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":8,"samples_ran":5,"samples_unverified":3,"pointer_only_for_licence":5,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/facenet-a-unified-embedding-for-face","title":"FaceNet: A Unified Embedding for Face Recognition and Clustering","date":"2015-03-12","rows_on_this_dataset":1,"code_links":183,"syntology":{"read_at":"2026-09-25T09:33:49+00:00","samples_harvested":154,"samples_ran":67,"samples_unverified":87,"pointer_only_for_licence":45,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-25T09:33:49+00:00","papers_with_samples":14,"samples_harvested":270,"samples_ran":146,"samples_unverified":124,"pointer_only_for_licence":82,"papers_with_no_sample_that_ran":2,"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."}