{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/tubetk-adopting-tubes-to-track-multi-object-1","title":"TubeTK: Adopting Tubes to Track Multi-Object in a One-Step Training Model","arxiv_id":"2006.05683","date":"2020-06-10","proceeding":"CVPR 2020 6","authors":["Bo Pang","Yizhuo Li","Yifan Zhang","Muchen Li","Cewu Lu"],"abstract":"Multi-object tracking is a fundamental vision problem that has been studied for a long time. As deep learning brings excellent performances to object detection algorithms, Tracking by Detection (TBD) has become the mainstream tracking framework. Despite the success of TBD, this two-step method is too complicated to train in an end-to-end manner and induces many challenges as well, such as insufficient exploration of video spatial-temporal information, vulnerability when facing object occlusion, and excessive reliance on detection results. To address these challenges, we propose a concise end-to-end model TubeTK which only needs one step training by introducing the ``bounding-tube\" to indicate temporal-spatial locations of objects in a short video clip. TubeTK provides a novel direction of multi-object tracking, and we demonstrate its potential to solve the above challenges without bells and whistles. We analyze the performance of TubeTK on several MOT benchmarks and provide empirical evidence to show that TubeTK has the ability to overcome occlusions to some extent without any ancillary technologies like Re-ID. Compared with other methods that adopt private detection results, our one-stage end-to-end model achieves state-of-the-art performances even if it adopts no ready-made detection results. We hope that the proposed TubeTK model can serve as a simple but strong alternative for video-based MOT task. The code and models are available at https://github.com/BoPang1996/TubeTK.","url_abs":"https://arxiv.org/abs/2006.05683v1","url_pdf":"https://arxiv.org/pdf/2006.05683v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"tubetk-adopting-tubes-to-track-multi-object-1","repo_url":"https://github.com/BoPang1996/TubeTK","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"multi-object-tracking","task_name":"Multi-Object Tracking"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-tracking","task_name":"Object Tracking"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"syntology_url":"https://syntology.ai/paper/2006.05683","atlas_url":"https://app.syntology.ai/?focus=2006.05683","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2006.05683"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-25T09:33:49+00:00","read_at_is":"when the build read Syntology's graph, not when any sample ran","claim":"Per-sample execution status on synthesized fixtures; not a correctness claim about the paper. Samples come from repositories linked to the paper, official or community; repo_kind says which.","repos":[{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/BoPang1996/TubeTK","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":13},"by_repo_kind":{"official":{"samples":13,"ran":0,"repositories":1}},"repo_kind_vocabulary":{"official":"The archive marks this repository official for the paper","named_in_paper":"The archive records that the paper mentions this repository; it is not marked official","listed":"In the archive's code links for this paper, not marked official and not recorded as mentioned in the paper","found_in_text":"Syntology found this repository in the paper's own text; whether it is the authors' implementation is not asserted","community":"Not in the archive's code links for this paper; a community repository Syntology harvested"},"n_pointer_only_for_licence":0,"samples":[{"code_sha256_prefix":"5bc06abceed1075f","entry":"boxiou","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Metrics.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Metrics.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"5bc06abceed1075f"}},{"code_sha256_prefix":"878384da3a1a8ee7","entry":"distance2bbox","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"network/utils.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/network/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"878384da3a1a8ee7"}},{"code_sha256_prefix":"0d548c0e307771fa","entry":"focal_loss","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"network/focal_loss.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/network/focal_loss.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"0d548c0e307771fa"}},{"code_sha256_prefix":"d516af542dfff21d","entry":"get_inter_box","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Visualization/Vis_Input.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Visualization/Vis_Input.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"d516af542dfff21d"}},{"code_sha256_prefix":"66cc6e4ab68b6398","entry":"get_seq_info_from_file_mot","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Visualization/Vis_Res.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Visualization/Vis_Res.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"66cc6e4ab68b6398"}},{"code_sha256_prefix":"cc0dce2102e162c9","entry":"giou_loss","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"network/utils.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/network/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"cc0dce2102e162c9"}},{"code_sha256_prefix":"1bcb91317c367710","entry":"iou_loss","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"network/utils.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/network/utils.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"1bcb91317c367710"}},{"code_sha256_prefix":"f64ce931dc5fac87","entry":"linear_sum_assignment_with_inf","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Metrics.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Metrics.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f64ce931dc5fac87"}},{"code_sha256_prefix":"f7898a5762a4d3e4","entry":"multi_apply","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"network/track_head.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/network/track_head.py","link_basis":"harvester_set","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"f7898a5762a4d3e4"}},{"code_sha256_prefix":"49cfe0b5c32b3793","entry":"one_hot_embedding","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"network/focal_loss.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/network/focal_loss.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"49cfe0b5c32b3793"}},{"code_sha256_prefix":"333a09225b53921f","entry":"parseSequences2","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Metrics.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Metrics.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"333a09225b53921f"}},{"code_sha256_prefix":"2c479e738ef20c41","entry":"tubes2bbox","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Visualization/Vis_Input.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Visualization/Vis_Input.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"2c479e738ef20c41"}},{"code_sha256_prefix":"17ad0accc3f687bf","entry":"tubes2bbox_out","repo":"BoPang1996/TubeTK","repo_kind":"official","path":"Visualization/Vis_Input.py","file_url":"https://github.com/BoPang1996/TubeTK/blob/HEAD/Visualization/Vis_Input.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"MIT","inline_ok":true,"mcp_get_code":{"code_sha256":"17ad0accc3f687bf"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}