{"url":"/dataset/kitti-mots","name":"KITTI MOTS","full_name":"KITTI Multi-Object Tracking and Segmentation (MOTS) Evaluation","description_markdown":"The Multi-Object and Segmentation (MOTS) benchmark [2] consists of 21 training sequences and 29 test sequences. It is based on the KITTI Tracking Evaluation 2012 and extends the annotations to the Multi-Object and Segmentation (MOTS) task. To this end, we added dense pixel-wise segmentation labels for every object. We evaluate submitted results using the metrics HOTA, CLEAR MOT, and MT/PT/ML. We rank methods by HOTA [1]. Our development kit and GitHub evaluation code provide details about the data format as well as utility functions for reading and writing the label files. (adapted for the segmentation case). Evaluation is performed using the code from the [TrackEval repository](https://github.com/JonathonLuiten/TrackEval).\r\n\r\n[1] J. Luiten, A. Os̆ep, P. Dendorfer, P. Torr, A. Geiger, L. Leal-Taixé, B. Leibe: [HOTA: A Higher Order Metric for Evaluating Multi-object Tracking.](https://link.springer.com/article/10.1007/s11263-020-01375-2) IJCV 2020.\r\n[2] P. Voigtlaender, M. Krause, A. Os̆ep, J. Luiten, B. Sekar, A. Geiger, B. Leibe: [MOTS: Multi-Object Tracking and Segmentation.](https://arxiv.org/pdf/1902.03604.pdf) CVPR 2019.","description_withheld":null,"homepage":"https://www.cvlibs.net/datasets/kitti/eval_mots.php","introduced_date":"2019-02-10","introduced_date_note":null,"introduced_by":{"paper":"/paper/mots-multi-object-tracking-and-segmentation","title":"MOTS: Multi-Object Tracking and Segmentation","first_author":"Paul Voigtlaender","url":null},"license":{"name":"Creative Commons Attribution-NonCommercial-ShareAlike 3.0","url":"https://creativecommons.org/licenses/by-nc-sa/3.0/"},"modalities":[{"name":"Images","url":"/datasets/modality/images"},{"name":"Videos","url":"/datasets/modality/videos"},{"name":"Tracking","url":"/datasets/modality/tracking"}],"tasks":[{"name":"2D Object Detection","url":"/task/2d-object-detection","datasets_with_task":"/datasets/task/2d-object-detection"},{"name":"2D Semantic Segmentation","url":"/task/2d-semantic-segmentation","datasets_with_task":"/datasets/task/2d-semantic-segmentation"},{"name":"Object Tracking","url":"/task/object-tracking","datasets_with_task":"/datasets/task/object-tracking"},{"name":"Multi-Object Tracking","url":"/task/multi-object-tracking","datasets_with_task":"/datasets/task/multi-object-tracking"},{"name":"Multiple Object Tracking","url":"/task/multiple-object-tracking","datasets_with_task":"/datasets/task/multiple-object-tracking"},{"name":"Multi-Object Tracking and Segmentation","url":"/task/multi-object-tracking-and-segmentation","datasets_with_task":"/datasets/task/multi-object-tracking-and-segmentation"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["KITTI MOTS"],"data_loaders":[],"num_papers_in_archive":28,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[{"leaderboard":"/sota/multi-object-tracking-and-segmentation-on-1","task":"Multi-Object Tracking and Segmentation","dataset_variant":"KITTI MOTS","rows":1,"metrics":["AssA","DetA","HOTA"],"first_row_in_archive_order":{"model":"EagerMOT","paper":"/paper/eagermot-3d-multi-object-tracking-via-sensor","metrics":{"AssA":"73.75","DetA":"76.11","HOTA":"74.66"},"code_links":[{"title":"aleksandrkim61/EagerMOT","url":"https://github.com/aleksandrkim61/EagerMOT"},{"title":"JrkJamie/eagermot_ms","url":"https://github.com/JrkJamie/eagermot_ms"},{"title":"gai-shaoyan/mind3d","url":"https://gitee.com/gai-shaoyan/mind3d"}]},"note":"rows are the archive's own order at snapshot; nothing here re-ranks them"}],"papers_with_a_benchmark_row":[{"paper":"/paper/eagermot-3d-multi-object-tracking-via-sensor","title":"EagerMOT: 3D Multi-Object Tracking via Sensor Fusion","date":"2021-04-29","rows_on_this_dataset":1,"code_links":3,"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."}}],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":1,"samples_harvested":4,"samples_ran":0,"samples_unverified":4,"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."}