{"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/seq-nms-for-video-object-detection","title":"Seq-NMS for Video Object Detection","arxiv_id":"1602.08465","date":"2016-02-26","proceeding":null,"authors":["Wei Han","Pooya Khorrami","Tom Le Paine","Prajit Ramachandran","Mohammad Babaeizadeh","Honghui Shi","Jianan Li","Shuicheng Yan","Thomas S. Huang"],"abstract":"Video object detection is challenging because objects that are easily\ndetected in one frame may be difficult to detect in another frame within the\nsame clip. Recently, there have been major advances for doing object detection\nin a single image. These methods typically contain three phases: (i) object\nproposal generation (ii) object classification and (iii) post-processing. We\npropose a modification of the post-processing phase that uses high-scoring\nobject detections from nearby frames to boost scores of weaker detections\nwithin the same clip. We show that our method obtains superior results to\nstate-of-the-art single image object detection techniques. Our method placed\n3rd in the video object detection (VID) task of the ImageNet Large Scale Visual\nRecognition Challenge 2015 (ILSVRC2015).","url_abs":"http://arxiv.org/abs/1602.08465v3","url_pdf":"http://arxiv.org/pdf/1602.08465v3.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":"seq-nms-for-video-object-detection","repo_url":"https://github.com/tmoopenn/seq-nms","is_official":0,"mentioned_in_paper":0,"mentioned_in_github":1,"framework":"none","reach":{"status":"ok","spdx":"MIT"}}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"object","task_name":"Object"},{"task_slug":"object-detection","task_name":"Object Detection"},{"task_slug":"object-proposal-generation","task_name":"Object Proposal Generation"},{"task_slug":"object-recognition","task_name":"Object Recognition"},{"task_slug":"video-object-detection","task_name":"Video 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=1602.08465","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"1602.08465"}},"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/tmoopenn/seq-nms","reach":{"status":"ok","spdx":"MIT"}}],"summary":{"unverified":1},"by_repo_kind":{"listed":{"samples":1,"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":"ec7af5ae0cd52328","entry":"find_best_sequence","repo":"tmoopenn/seq-nms","repo_kind":"listed","path":"seq_nms.py","file_url":"https://github.com/tmoopenn/seq-nms/blob/HEAD/seq_nms.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":"ec7af5ae0cd52328"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}