{"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/sports-video-analysis-on-large-scale-data","title":"Sports Video Analysis on Large-Scale Data","arxiv_id":"2208.04897","date":"2022-08-09","proceeding":null,"authors":["Dekun Wu","He Zhao","Xingce Bao","Richard P. Wildes"],"abstract":"This paper investigates the modeling of automated machine description on sports video, which has seen much progress recently. Nevertheless, state-of-the-art approaches fall quite short of capturing how human experts analyze sports scenes. There are several major reasons: (1) The used dataset is collected from non-official providers, which naturally creates a gap between models trained on those datasets and real-world applications; (2) previously proposed methods require extensive annotation efforts (i.e., player and ball segmentation at pixel level) on localizing useful visual features to yield acceptable results; (3) very few public datasets are available. In this paper, we propose a novel large-scale NBA dataset for Sports Video Analysis (NSVA) with a focus on captioning, to address the above challenges. We also design a unified approach to process raw videos into a stack of meaningful features with minimum labelling efforts, showing that cross modeling on such features using a transformer architecture leads to strong performance. In addition, we demonstrate the broad application of NSVA by addressing two additional tasks, namely fine-grained sports action recognition and salient player identification. Code and dataset are available at https://github.com/jackwu502/NSVA.","url_abs":"https://arxiv.org/abs/2208.04897v1","url_pdf":"https://arxiv.org/pdf/2208.04897v1.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":"sports-video-analysis-on-large-scale-data","repo_url":"https://github.com/jackwu502/nsva","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":0,"framework":"pytorch","reach":null}],"tasks":[{"task_slug":"action-recognition-in-videos","task_name":"Action Recognition"}],"methods":[],"datasets_introduced":[{"slug":"nsva","name":"NSVA","full_name":"NBA dataset for Sports Video Analysis"}],"methods_introduced":[],"results":[],"syntology":{"atlas_url":"https://app.syntology.ai/?focus=2208.04897","mcp":{"get_harvested_code_for_paper":{"arxiv_id":"2208.04897"}},"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/jackwu502/nsva","reach":null},{"provenance":"deterministic:regex_extraction","url":"https://github.com/jackwu502/NSVA","reach":null}],"summary":{"ran_draft_wrong":1,"ran_fixture":1,"unverified":3},"by_repo_kind":{"official":{"samples":4,"ran":1,"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":5,"samples":[{"code_sha256_prefix":"b757d4deaba5dc8c","entry":"get_args","repo":"jackwu502/NSVA","repo_kind":"official","path":"SportsFormer/main_task_player_multifeat.py","file_url":"https://github.com/jackwu502/NSVA/blob/HEAD/SportsFormer/main_task_player_multifeat.py","link_basis":"first_harvest_node","language":"python","status":"ran_draft_wrong","verification_level":1,"contract_check":"OUTPUT_MISDECLARED","metamorphic_tier":"deterministic","behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"b757d4deaba5dc8c"}},{"code_sha256_prefix":"a0c23f10479a984e","entry":"init_device","repo":null,"repo_kind":null,"path":null,"file_url":null,"link_basis":"identical_code_first_harvested_elsewhere","language":"python","status":"ran_fixture","verification_level":1,"contract_check":"RAISES","metamorphic_tier":null,"behaviour_fingerprint":false,"licence":null,"inline_ok":false,"mcp_get_code":{"code_sha256":"a0c23f10479a984e"}},{"code_sha256_prefix":"80c212f41c6c0428","entry":"get_args","repo":"jackwu502/nsva","repo_kind":"official","path":"SportsFormer/main_task_caption.py","file_url":"https://github.com/jackwu502/nsva/blob/HEAD/SportsFormer/main_task_caption.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"80c212f41c6c0428"}},{"code_sha256_prefix":"569c79c5dc9f8524","entry":"get_args","repo":"jackwu502/NSVA","repo_kind":"official","path":"SportsFormer/main_task_action_multifeat_multilevel.py","file_url":"https://github.com/jackwu502/NSVA/blob/HEAD/SportsFormer/main_task_action_multifeat_multilevel.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"569c79c5dc9f8524"}},{"code_sha256_prefix":"86658d6cfae56ed3","entry":"set_seed_logger","repo":"jackwu502/nsva","repo_kind":"official","path":"SportsFormer/main_task_action_multifeat_multilevel.py","file_url":"https://github.com/jackwu502/nsva/blob/HEAD/SportsFormer/main_task_action_multifeat_multilevel.py","link_basis":"first_harvest_node","language":"python","status":"unverified","verification_level":0,"contract_check":null,"metamorphic_tier":null,"behaviour_fingerprint":false,"licence":"NONE","inline_ok":false,"mcp_get_code":{"code_sha256":"86658d6cfae56ed3"}}]},"arxiv_metadata":null,"syntology_extracted_results":null}