{"url":"/dataset/mot20","name":"MOT20","full_name":"MOT20","description_markdown":"**MOT20** is a dataset for multiple object tracking. The dataset contains 8 challenging video sequences (4 train, 4 test) in unconstrained environments, from crowded places such as train stations, town squares and a sports stadium.\nImage Source: [https://motchallenge.net/vis/MOT20-04](https://motchallenge.net/vis/MOT20-04)","description_withheld":null,"homepage":"https://motchallenge.net/data/MOT20/","introduced_date":null,"introduced_date_note":null,"introduced_by":null,"license":null,"modalities":[{"name":"Videos","url":"/datasets/modality/videos"}],"tasks":[{"name":"Multi-Object Tracking","url":"/task/multi-object-tracking","datasets_with_task":"/datasets/task/multi-object-tracking"},{"name":"Multiple Object Tracking with Transformer","url":"/task/multiple-object-tracking-with-transformer","datasets_with_task":"/datasets/task/multiple-object-tracking-with-transformer"}],"languages":[],"variants":["MOT20"],"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":34,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-object-tracking-on-mot20-1","task":"Multi-Object Tracking","dataset_variant":"MOT20","rows":27,"metrics":["HOTA","MOTA","IDF1","AssA","Speed (FPS)"],"first_row_in_archive_order":{"model":"BoostTrack++","paper":"/paper/boosttrack-using-tracklet-information-to","metrics":{"HOTA":"66.4","IDF1":"82","MOTA":"77.7"},"code_links":[{"title":"mikel-brostrom/boxmot","url":"https://github.com/mikel-brostrom/boxmot"},{"title":"vukasin-stanojevic/BoostTrack","url":"https://github.com/vukasin-stanojevic/BoostTrack"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"},{"leaderboard":"/sota/multiple-object-tracking-with-transformer-on","task":"Multiple Object Tracking with Transformer","dataset_variant":"MOT20","rows":1,"metrics":["HOTA","MOTA","IDF1"],"first_row_in_archive_order":{"model":"STC_pub","paper":"/paper/strong-transcenter-improved-multi-object","metrics":{"HOTA":"56.1","IDF1":"67.6","MOTA":"73.0"},"code_links":[{"title":"amitgalor18/stc_tracker","url":"https://github.com/amitgalor18/stc_tracker"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/focusing-on-tracks-for-online-multi-object","title":"Focusing on Tracks for Online Multi-Object Tracking","date":"2025-06-15","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/hoptrack-a-real-time-multi-object-tracking","title":"HopTrack: A Real-time Multi-Object Tracking System for Embedded Devices","date":"2024-11-01","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/adaptrack-adaptive-thresholding-based","title":"AdapTrack: Adaptive Thresholding-Based Matching For Multi-object Tracking","date":"2024-09-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/a-confidence-aware-matching-strategy-for","title":"A Confidence-Aware Matching Strategy For Generalized Multi-Object Tracking","date":"2024-09-27","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/when-to-extract-reid-features-a-selective","title":"When to Extract ReID Features: A Selective Approach for Improved Multiple Object Tracking","date":"2024-09-10","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/interacting-multiple-model-based-joint","title":"One Homography is All You Need: IMM-based Joint Homography and Multiple Object State Estimation","date":"2024-09-04","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/boosttrack-using-tracklet-information-to","title":"BoostTrack++: using tracklet information to detect more objects in multiple object tracking","date":"2024-08-23","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/boosttrack-boosting-the-similarity-measure","title":"BoostTrack: boosting the similarity measure and detection confidence for improved multiple object tracking","date":"2024-04-12","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sfsort-scene-features-based-simple-online","title":"SFSORT: Scene Features-based Simple Online Real-Time Tracker","date":"2024-04-11","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/ucmctrack-multi-object-tracking-with-uniform","title":"UCMCTrack: Multi-Object Tracking with Uniform Camera Motion Compensation","date":"2023-12-14","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/sparsetrack-multi-object-tracking-by","title":"SparseTrack: Multi-Object Tracking by Performing Scene Decomposition based on Pseudo-Depth","date":"2023-06-08","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/deep-oc-sort-multi-pedestrian-tracking-by","title":"Deep OC-SORT: Multi-Pedestrian Tracking by Adaptive Re-Identification","date":"2023-02-23","rows_on_this_dataset":1,"code_links":3,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":2,"samples_unverified":8,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/smiletrack-similarity-learning-for-multiple","title":"SMILEtrack: SiMIlarity LEarning for Occlusion-Aware Multiple Object Tracking","date":"2022-11-16","rows_on_this_dataset":1,"code_links":2,"syntology":null},{"paper":"/paper/strong-transcenter-improved-multi-object","title":"Strong-TransCenter: Improved Multi-Object Tracking based on Transformers with Dense Representations","date":"2022-10-24","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/multiple-object-tracking-from-appearance-by","title":"Multiple Object Tracking from appearance by hierarchically clustering tracklets","date":"2022-10-07","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/lmot-efficient-light-weight-detection-and","title":"LMOT: Efficient Light-Weight Detection and Tracking in Crowds","date":"2022-08-08","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/bot-sort-robust-associations-multi-pedestrian","title":"BoT-SORT: Robust Associations Multi-Pedestrian Tracking","date":"2022-06-29","rows_on_this_dataset":1,"code_links":7,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":10,"samples_ran":4,"samples_unverified":6,"pointer_only_for_licence":1,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/detection-recovery-in-online-multi-object","title":"Detection Recovery in Online Multi-Object Tracking with Sparse Graph Tracker","date":"2022-05-02","rows_on_this_dataset":1,"code_links":1,"syntology":null},{"paper":"/paper/observation-centric-sort-rethinking-sort-for","title":"Observation-Centric SORT: Rethinking SORT for Robust Multi-Object Tracking","date":"2022-03-27","rows_on_this_dataset":1,"code_links":7,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":31,"samples_ran":15,"samples_unverified":16,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/simpletrack-rethinking-and-improving-the-jde","title":"SimpleTrack: Rethinking and Improving the JDE Approach for Multi-Object Tracking","date":"2022-03-08","rows_on_this_dataset":1,"code_links":6,"syntology":null},{"paper":"/paper/strongsort-make-deepsort-great-again","title":"StrongSORT: Make DeepSORT Great Again","date":"2022-02-28","rows_on_this_dataset":1,"code_links":14,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":20,"samples_ran":3,"samples_unverified":17,"pointer_only_for_licence":2,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"paper":"/paper/online-multi-object-tracking-with","title":"Online Multi-Object Tracking with Unsupervised Re-Identification Learning and Occlusion Estimation","date":"2022-01-04","rows_on_this_dataset":1,"code_links":0,"syntology":null},{"paper":"/paper/bytetrack-multi-object-tracking-by-1","title":"ByteTrack: Multi-Object Tracking by Associating Every Detection Box","date":"2021-10-13","rows_on_this_dataset":1,"code_links":10,"syntology":{"read_at":"2026-09-24T18:15:14+00:00","samples_harvested":12,"samples_ran":1,"samples_unverified":11,"pointer_only_for_licence":0,"claim":"Per-sample execution on synthesized fixtures; not a correctness claim."}},{"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/2103-15145","title":"TransCenter: Transformers with Dense Representations for Multiple-Object Tracking","date":"2021-03-28","rows_on_this_dataset":1,"code_links":2,"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."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":6,"samples_harvested":136,"samples_ran":33,"samples_unverified":103,"pointer_only_for_licence":5,"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."}