{"url":"/dataset/bts3-1","name":"BTS3.1","full_name":"Expanding Accurate Person Recognition to New Altitudes and Ranges: The BRIAR Dataset","description_markdown":"Large, multimodal biometric dataset: It contains still images and videos of over 1,000 people captured at various ranges (up to 1,000 meters) and elevations (up to 400 meters) using a diverse set of cameras (commercial, military-grade, specialized).\r\n\r\nFocus on challenging scenarios: Designed to address limitations of existing datasets, it includes data with extreme poses, low resolutions, and atmospheric distortions to push the boundaries of biometric recognition algorithms.\r\n\r\nRich annotations and diversity: Each data point is accompanied by detailed metadata (sensor details, weather conditions) and manual annotations (bounding boxes, yaw/pitch angles) for face and whole-body regions. The dataset also ensures demographic diversity for robust algorithm development.","description_withheld":null,"homepage":"https://www.iarpa.gov/research-programs/briar","introduced_date":"2023-01-01","introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Person Re-Identification","url":"/task/person-re-identification","datasets_with_task":"/datasets/task/person-re-identification"},{"name":"Face Recognition","url":"/task/face-recognition","datasets_with_task":"/datasets/task/face-recognition"},{"name":"Face Verification","url":"/task/face-verification","datasets_with_task":"/datasets/task/face-verification"},{"name":"Lightweight Face Recognition","url":"/task/lightweight-face-recognition","datasets_with_task":"/datasets/task/lightweight-face-recognition"},{"name":"Face Image Retrieval","url":"/task/face-image-retrieval","datasets_with_task":"/datasets/task/face-image-retrieval"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["BTS3.1"],"data_loaders":[],"num_papers_in_archive":5,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/face-verification-on-bts3-1","task":"Face Verification","dataset_variant":"BTS3.1","rows":7,"metrics":["TAR @ FAR=0.01"],"first_row_in_archive_order":{"model":"ProxyFusion (Adaface)","paper":"/paper/proxyfusion-face-feature-aggregation-through","metrics":{"TAR @ FAR=0.01":"0.689"},"code_links":[{"title":"bhavinjawade/proxyfusion","url":"https://github.com/bhavinjawade/proxyfusion"},{"title":"bhavinjawade/ProxyFusion-NeurIPS","url":"https://github.com/bhavinjawade/ProxyFusion-NeurIPS"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/face-recognition-on-bts3-1","task":"Face Recognition","dataset_variant":"BTS3.1","rows":1,"metrics":["TAR @ FAR=0.01"],"first_row_in_archive_order":{"model":"MCN","paper":"/paper/multicolumn-networks-for-face-recognition","metrics":{"TAR @ FAR=0.01":"0.5425"},"code_links":[{"title":"ibendrup/MulticolumnNetwork","url":"https://github.com/ibendrup/MulticolumnNetwork"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/proxyfusion-face-feature-aggregation-through","title":"ProxyFusion: Face Feature Aggregation Through Sparse Experts","date":"2025-09-24","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/conan-conditional-neural-aggregation-network","title":"CoNAN: Conditional Neural Aggregation Network For Unconstrained Face Feature Fusion","date":"2023-07-16","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"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":"2026-09-24T18:15:14+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/multicolumn-networks-for-face-recognition","title":"Multicolumn Networks for Face Recognition","date":"2018-07-24","rows_on_this_dataset":2,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+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/neural-aggregation-network-for-video-face","title":"Neural Aggregation Network for Video Face Recognition","date":"2016-03-17","rows_on_this_dataset":3,"code_links":0,"syntology":null}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":2,"samples_harvested":13,"samples_ran":7,"samples_unverified":6,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":1,"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."}