{"url":"/dataset/taxibj","name":"TaxiBJ","full_name":null,"description_markdown":"TaxiBJ consists of trajectory data from taxicab GPS data and meteorology data in Beijing from four time intervals: 1st Jul. 2013 - 30th Otc. 2013, 1st Mar. 2014 - 30th Jun. 2014, 1st Mar. 2015 - 30th Jun. 2015, 1st Nov. 2015 - 10th Apr. 2016. \r\n\r\nSource: [https://arxiv.org/pdf/1701.02543.pdf](https://arxiv.org/pdf/1701.02543.pdf)","description_withheld":null,"homepage":"https://github.com/TolicWang/DeepST/tree/master/data/TaxiBJ","introduced_date":"2016-10-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/deep-spatio-temporal-residual-networks-for","title":"Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction","first_author":"Junbo Zhang","url":null},"license":{"name":"Unknown","url":null},"modalities":[{"name":"Images","url":"/datasets/modality/images"}],"tasks":[{"name":"Fine-Grained Urban Flow Inference","url":"/task/fine-grained-urban-flow-inference","datasets_with_task":"/datasets/task/fine-grained-urban-flow-inference"}],"languages":[],"variants":["TaxiBJ","TaxiBJ-P1","TaxiBJ-P2","TaxiBJ-P3","TaxiBJ-P4"],"data_loaders":[{"repo":"https://github.com/snehasinghania/STResNet","url":"https://github.com/snehasinghania/STResNet","frameworks":["pytorch"]}],"num_papers_in_archive":62,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/fine-grained-urban-flow-inference-on-taxibj-1","task":"Fine-Grained Urban Flow Inference","dataset_variant":"TaxiBJ-P2","rows":3,"metrics":["MSE ","MAE","MAPE"],"first_row_in_archive_order":{"model":"STCF","paper":"/paper/spatial-temporal-contrasting-for-fine-grained","metrics":{"MSE ":"18.2566"},"code_links":[{"title":"Xovee/stcf","url":"https://github.com/Xovee/stcf"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fine-grained-urban-flow-inference-on-taxibj-3","task":"Fine-Grained Urban Flow Inference","dataset_variant":"TaxiBJ-P4","rows":3,"metrics":["MSE ","MAE","MAPE"],"first_row_in_archive_order":{"model":"STCF","paper":"/paper/spatial-temporal-contrasting-for-fine-grained","metrics":{"MSE ":"11.7718"},"code_links":[{"title":"Xovee/stcf","url":"https://github.com/Xovee/stcf"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/fine-grained-urban-flow-inference-on-taxibj-2","task":"Fine-Grained Urban Flow Inference","dataset_variant":"TaxiBJ-P3","rows":2,"metrics":["MSE","MAE","MAPE"],"first_row_in_archive_order":{"model":"STCF","paper":"/paper/spatial-temporal-contrasting-for-fine-grained","metrics":{"MSE":"19.4153"},"code_links":[{"title":"Xovee/stcf","url":"https://github.com/Xovee/stcf"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/spatial-temporal-contrasting-for-fine-grained","title":"Spatial-Temporal Contrasting for Fine-Grained Urban Flow Inference","date":"2023-12-01","rows_on_this_dataset":3,"code_links":1,"syntology":null},{"paper":"/paper/urbanfm-inferring-fine-grained-urban-flows","title":"UrbanFM: Inferring Fine-Grained Urban Flows","date":"2019-02-06","rows_on_this_dataset":5,"code_links":1,"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."}