{"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/detect-to-track-and-track-to-detect","title":"Detect to Track and Track to Detect","arxiv_id":"1710.03958","date":"2017-10-11","proceeding":"ICCV 2017 10","authors":["Christoph Feichtenhofer","Axel Pinz","Andrew Zisserman"],"abstract":"Recent approaches for high accuracy detection and tracking of object\ncategories in video consist of complex multistage solutions that become more\ncumbersome each year. In this paper we propose a ConvNet architecture that\njointly performs detection and tracking, solving the task in a simple and\neffective way. Our contributions are threefold: (i) we set up a ConvNet\narchitecture for simultaneous detection and tracking, using a multi-task\nobjective for frame-based object detection and across-frame track regression;\n(ii) we introduce correlation features that represent object co-occurrences\nacross time to aid the ConvNet during tracking; and (iii) we link the frame\nlevel detections based on our across-frame tracklets to produce high accuracy\ndetections at the video level. Our ConvNet architecture for spatiotemporal\nobject detection is evaluated on the large-scale ImageNet VID dataset where it\nachieves state-of-the-art results. Our approach provides better single model\nperformance than the winning method of the last ImageNet challenge while being\nconceptually much simpler. Finally, we show that by increasing the temporal\nstride we can dramatically increase the tracker speed.","url_abs":"http://arxiv.org/abs/1710.03958v2","url_pdf":"http://arxiv.org/pdf/1710.03958v2.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":"detect-to-track-and-track-to-detect","repo_url":"https://github.com/feichtenhofer/detect-track","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"none","reach":{"status":"ok","spdx":"NOASSERTION"}},{"paper_slug":"detect-to-track-and-track-to-detect","repo_url":"https://github.com/Feynman27/pytorch-detect-to-track","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":{"status":"ok","spdx":"MIT"}},{"paper_slug":"detect-to-track-and-track-to-detect","repo_url":"https://github.com/jfc4050/detect-to-track","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-detection-1","task_name":"object-detection"}],"methods":[],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=1710.03958","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1710.03958"}},"developers":"https://syntology.ai/developers","read_at":"2026-09-24T18:15:14+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/jfc4050/detect-to-track","reach":null},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/feichtenhofer/detect-track","reach":{"status":"ok","spdx":"NOASSERTION"}},{"provenance":"external:paperswithcode_snapshot_2025-07-28","url":"https://github.com/Feynman27/pytorch-detect-to-track","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":4},"by_repo_kind":{"listed":{"samples":4,"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":"3be9228820b46ef3","entry":"get_imdb","repo":"Feynman27/pytorch-detect-to-track","repo_kind":"listed","path":"lib/datasets/factory.py","file_url":"https://github.com/Feynman27/pytorch-detect-to-track/blob/HEAD/lib/datasets/factory.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":"3be9228820b46ef3"}},{"code_sha256_prefix":"8a015c012f507631","entry":"unique_boxes","repo":"Feynman27/pytorch-detect-to-track","repo_kind":"listed","path":"lib/datasets/ds_utils.py","file_url":"https://github.com/Feynman27/pytorch-detect-to-track/blob/HEAD/lib/datasets/ds_utils.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":"8a015c012f507631"}},{"code_sha256_prefix":"d3e019b11b709edb","entry":"xywh_to_xyxy","repo":"Feynman27/pytorch-detect-to-track","repo_kind":"listed","path":"lib/datasets/ds_utils.py","file_url":"https://github.com/Feynman27/pytorch-detect-to-track/blob/HEAD/lib/datasets/ds_utils.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":"d3e019b11b709edb"}},{"code_sha256_prefix":"a832e5017f504280","entry":"xyxy_to_xywh","repo":"Feynman27/pytorch-detect-to-track","repo_kind":"listed","path":"lib/datasets/ds_utils.py","file_url":"https://github.com/Feynman27/pytorch-detect-to-track/blob/HEAD/lib/datasets/ds_utils.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":"a832e5017f504280"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}