{"url":"/dataset/mot15","name":"MOT15","full_name":"Multiple Object Tracking 15","description_markdown":"MOT2015 is a dataset for multiple object tracking. It contains 11 different indoor and outdoor scenes of public places with pedestrians as the objects of interest, where camera motion, camera angle and imaging condition vary greatly. The dataset provides detections generated by the ACF-based detector.\r\n\r\nSource: [FAMNet: Joint Learning of Feature, Affinity and Multi-dimensional Assignment for Online Multiple Object Tracking](https://arxiv.org/abs/1904.04989)\r\nImage Source: [https://www.researchgate.net/figure/Exemplary-qualitative-tracking-results-for-the-MOT15-benchmark-dataset-a-d-are-from-a_fig1_340328377](https://www.researchgate.net/figure/Exemplary-qualitative-tracking-results-for-the-MOT15-benchmark-dataset-a-d-are-from-a_fig1_340328377)","description_withheld":null,"homepage":"https://motchallenge.net/results/2D_MOT_2015/","introduced_date":"2015-01-01","introduced_date_note":null,"introduced_by":{"paper":"/paper/motchallenge-2015-towards-a-benchmark-for","title":"MOTChallenge 2015: Towards a Benchmark for Multi-Target Tracking","first_author":"Laura Leal-Taixé","url":null},"license":{"name":"CC BY-NC-SA 3.0","url":"https://creativecommons.org/licenses/by-nc-sa/3.0/"},"modalities":[{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Tracking","url":"/datasets/modality/tracking"}],"tasks":[{"name":"Multi-Object Tracking","url":"/task/multi-object-tracking","datasets_with_task":"/datasets/task/multi-object-tracking"},{"name":"Online Multi-Object Tracking","url":"/task/online-multi-object-tracking","datasets_with_task":"/datasets/task/online-multi-object-tracking"}],"languages":[],"variants":["2DMOT15","2D MOT 2015","MOT15"],"data_loaders":[{"repo":"https://github.com/open-mmlab/mmtracking","url":"https://github.com/open-mmlab/mmtracking/blob/master/docs/dataset.md","frameworks":["pytorch"]}],"num_papers_in_archive":67,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-object-tracking-on-2d-mot-2015","task":"Multi-Object Tracking","dataset_variant":"2D MOT 2015","rows":4,"metrics":["MOTA","IDF1"],"first_row_in_archive_order":{"model":"GSDT","paper":"/paper/joint-detection-and-multi-object-tracking","metrics":{"MOTA":"60.7"},"code_links":[{"title":"yongxinw/GSDT","url":"https://github.com/yongxinw/GSDT"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-object-tracking-on-2dmot15-1","task":"Multi-Object Tracking","dataset_variant":"2DMOT15","rows":2,"metrics":["MOTA","IDF1"],"first_row_in_archive_order":{"model":"FairMOT","paper":"/paper/a-simple-baseline-for-multi-object-tracking","metrics":{"MOTA":"60.6"},"code_links":[{"title":"PaddlePaddle/PaddleDetection","url":"https://github.com/PaddlePaddle/PaddleDetection"},{"title":"ifzhang/FairMOT","url":"https://github.com/ifzhang/FairMOT"},{"title":"mindspore-ai/models","url":"https://github.com/mindspore-ai/models/tree/master/research/cv/fairmot"},{"title":"microsoft/FairMOT","url":"https://github.com/microsoft/FairMOT"},{"title":"microsoft/UDA","url":"https://github.com/microsoft/UDA"},{"title":"nolanzzz/MTMCT","url":"https://github.com/nolanzzz/MTMCT"},{"title":"chen-si-jia/Trajectory-Long-tail-Distribution-for-MOT","url":"https://github.com/chen-si-jia/Trajectory-Long-tail-Distribution-for-MOT"},{"title":"zengwbz/Face-Tracking-usingFairMOT","url":"https://github.com/zengwbz/Face-Tracking-usingFairMOT"},{"title":"dingwoai/FairMOT-BDD100K","url":"https://github.com/dingwoai/FairMOT-BDD100K"},{"title":"ydhcg-bobo/stcmot","url":"https://github.com/ydhcg-bobo/stcmot"},{"title":"harsh2912/people-tracking","url":"https://github.com/harsh2912/people-tracking"},{"title":"dhu-mmct/dhu-mmct","url":"https://github.com/dhu-mmct/dhu-mmct"},{"title":"cds-mipt/cds-tracking","url":"https://github.com/cds-mipt/cds-tracking"},{"title":"seominseok0429/vidoe_tracking-Reidentification-Action_recognition_Demo","url":"https://github.com/seominseok0429/vidoe_tracking-Reidentification-Action_recognition_Demo"},{"title":"ZJUT-ERCISS/zjut_mindvideo","url":"https://github.com/ZJUT-ERCISS/zjut_mindvideo/blob/master/msvideo/models/fairmot.py"},{"title":"ankitsinghsuraj/mot20","url":"https://github.com/ankitsinghsuraj/mot20"},{"title":"MindSpore-paper-code-3/code10","url":"https://github.com/MindSpore-paper-code-3/code10/tree/main/fairmot"},{"title":"nadinenijssen/Github_5AUA0_Project_G12T1","url":"https://github.com/nadinenijssen/Github_5AUA0_Project_G12T1"},{"title":"oljikeboost/PlayerTracking","url":"https://github.com/oljikeboost/PlayerTracking"},{"title":"MindSpore-paper-code-3/code3","url":"https://github.com/MindSpore-paper-code-3/code3/tree/main/fairmot"},{"title":"lilin19890401/FairMOT","url":"https://github.com/lilin19890401/FairMOT"},{"title":"MindSpore-paper-code-3/code8","url":"https://github.com/MindSpore-paper-code-3/code8/tree/main/fairmot"},{"title":"nemonameless/fairmot","url":"https://github.com/nemonameless/fairmot"},{"title":"MindSpore-paper-code-3/code7","url":"https://github.com/MindSpore-paper-code-3/code7/tree/main/fairmot"},{"title":"15534081591/FairMOT","url":"https://github.com/15534081591/FairMOT"},{"title":"FlorentijnD/FairMOT","url":"https://github.com/FlorentijnD/FairMOT"},{"title":"Bangbangbanana/fairmot_mindspore","url":"https://github.com/Bangbangbanana/fairmot_mindspore"},{"title":"gsan2/FairMOT","url":"https://github.com/gsan2/FairMOT"},{"title":"HoganZhang/FairMOT","url":"https://github.com/HoganZhang/FairMOT"},{"title":"IMBINGO95/FairMOT","url":"https://github.com/IMBINGO95/FairMOT"},{"title":"jingcjie/FairMOT-mindspore-jupyter","url":"https://github.com/jingcjie/FairMOT-mindspore-jupyter"},{"title":"realdingke/mscai_softwareengineering_project","url":"https://github.com/realdingke/mscai_softwareengineering_project"},{"title":"Mind23-2/MindCode-42","url":"https://github.com/Mind23-2/MindCode-42"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multi-object-tracking-on-mot15","task":"Multi-Object Tracking","dataset_variant":"MOT15","rows":2,"metrics":["MOTA","MOTP"],"first_row_in_archive_order":{"model":"Baseline+MFW","paper":"/paper/track-to-detect-and-segment-an-online-multi","metrics":{"MOTA":"66.5"},"code_links":[{"title":"JialianW/TraDeS","url":"https://github.com/JialianW/TraDeS"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/online-multi-object-tracking-on-2d-mot-2015","task":"Online Multi-Object Tracking","dataset_variant":"2D MOT 2015","rows":1,"metrics":["MOTA"],"first_row_in_archive_order":{"model":"Tracktor++","paper":"/paper/tracking-without-bells-and-whistles","metrics":{"MOTA":"44.1"},"code_links":[{"title":"phil-bergmann/tracking_wo_bnw","url":"https://github.com/phil-bergmann/tracking_wo_bnw"},{"title":"dvl-tum/mot_neural_solver","url":"https://github.com/dvl-tum/mot_neural_solver"},{"title":"mhnasseri/sort_oh","url":"https://github.com/mhnasseri/sort_oh"},{"title":"dvl-tum/motsynth-baselines","url":"https://github.com/dvl-tum/motsynth-baselines"},{"title":"xiuyu0000/new_papers_codes","url":"https://github.com/xiuyu0000/new_papers_codes/tree/main/rbpn"},{"title":"a-doering/tracker_w_correlation_motion_model","url":"https://github.com/a-doering/tracker_w_correlation_motion_model"},{"title":"2023-MindSpore-1/ms-code-217","url":"https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tracktor"},{"title":"2023-MindSpore-1/ms-code-217","url":"https://github.com/2023-MindSpore-1/ms-code-217/tree/main/tracktor%2B%2B"},{"title":"2023-MindSpore-1/ms-code-7","url":"https://github.com/2023-MindSpore-1/ms-code-7/tree/main/tracktor%2B%2B"},{"title":"MkuuWaUjinga/Self-Supervised-Learning-for-Tracktor","url":"https://github.com/MkuuWaUjinga/Self-Supervised-Learning-for-Tracktor"},{"title":"LKLQQ/tracktor","url":"https://github.com/LKLQQ/tracktor"},{"title":"MindSpore-paper-code-2/code3","url":"https://github.com/MindSpore-paper-code-2/code3/tree/main/tracktor%2B%2B"},{"title":"HoganZhang/mot_neural_solver","url":"https://github.com/HoganZhang/mot_neural_solver"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/online-multi-object-tracking-on-mot15","task":"Online Multi-Object Tracking","dataset_variant":"MOT15","rows":1,"metrics":["MOTA"],"first_row_in_archive_order":{"model":"GMPHD Filter (Occlusion Group Management)","paper":"/paper/online-multi-object-tracking-framework-with","metrics":{"MOTA":"30.7"},"code_links":[{"title":"SonginCV/GMPHD-OGM_Tracker","url":"https://github.com/SonginCV/GMPHD-OGM_Tracker"},{"title":"SonginCV/MAF_HDA","url":"https://github.com/SonginCV/MAF_HDA"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/spatial-temporal-graph-transformer-for","title":"TransMOT: Spatial-Temporal Graph Transformer for Multiple Object Tracking","date":"2021-04-01","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/track-to-detect-and-segment-an-online-multi","title":"Track to Detect and Segment: An Online Multi-Object Tracker","date":"2021-03-16","rows_on_this_dataset":1,"code_links":1,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":4,"samples_ran":4,"samples_unverified":0,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/lifted-disjoint-paths-with-application-in-1","title":"Lifted Disjoint Paths with Application in Multiple Object Tracking","date":"2020-06-25","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/joint-detection-and-multi-object-tracking","title":"Joint Object Detection and Multi-Object Tracking with Graph Neural Networks","date":"2020-06-23","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/learning-a-neural-solver-for-multiple-object-1","title":"Learning a Neural Solver for Multiple Object Tracking","date":"2020-06-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-simple-baseline-for-multi-object-tracking","title":"FairMOT: On the Fairness of Detection and Re-Identification in Multiple Object Tracking","date":"2020-04-04","rows_on_this_dataset":1,"code_links":33,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":53,"samples_ran":8,"samples_unverified":45,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/online-multi-object-tracking-framework-with","title":"Online Multi-Object Tracking Framework with the GMPHD Filter and Occlusion Group Management","date":"2019-07-31","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/deepmot-a-differentiable-framework-for","title":"How To Train Your Deep Multi-Object Tracker","date":"2019-06-15","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/tracking-without-bells-and-whistles","title":"Tracking without bells and whistles","date":"2019-03-13","rows_on_this_dataset":1,"code_links":13,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":14,"samples_ran":3,"samples_unverified":11,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/simple-online-and-realtime-tracking","title":"Simple Online and Realtime Tracking","date":"2016-02-02","rows_on_this_dataset":1,"code_links":56,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":40,"samples_ran":15,"samples_unverified":25,"pointer_only_for_licence":7,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":4,"samples_harvested":111,"samples_ran":30,"samples_unverified":81,"pointer_only_for_licence":9,"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."}