{"id":"https://openalex.org/W2980754694","doi":"https://doi.org/10.1145/3347318.3355517","title":"Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup","display_name":"Real-time CNN-based Segmentation Architecture for Ball Detection in a Single View Setup","publication_year":2019,"publication_date":"2019-10-15","ids":{"openalex":"https://openalex.org/W2980754694","doi":"https://doi.org/10.1145/3347318.3355517","mag":"2980754694"},"language":"en","primary_location":{"id":"doi:10.1145/3347318.3355517","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3347318.3355517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2007.11876","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5058349515","display_name":"Gabriel Van Zandycke","orcid":"https://orcid.org/0000-0002-8384-4166"},"institutions":[{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE"],"is_corresponding":true,"raw_author_name":"Gabriel Van Zandycke","raw_affiliation_strings":["Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5012049713","display_name":"Christophe De Vleeschouwer","orcid":"https://orcid.org/0000-0001-5049-2929"},"institutions":[{"id":"https://openalex.org/I95674353","display_name":"UCLouvain","ror":"https://ror.org/02495e989","country_code":"BE","type":"education","lineage":["https://openalex.org/I95674353"]}],"countries":["BE"],"is_corresponding":false,"raw_author_name":"Christophe De Vleeschouwer","raw_affiliation_strings":["Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium"],"affiliations":[{"raw_affiliation_string":"Universit\u00e9 catholique de Louvain, Louvain-la-Neuve, Belgium","institution_ids":["https://openalex.org/I95674353"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5058349515"],"corresponding_institution_ids":["https://openalex.org/I95674353"],"apc_list":null,"apc_paid":null,"fwci":0.7216,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.79177843,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"51","last_page":"58"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9983999729156494,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11439","display_name":"Video Analysis and Summarization","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.992900013923645,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.7988390922546387},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.797357439994812},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7864886522293091},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6425200700759888},{"id":"https://openalex.org/keywords/ball","display_name":"Ball (mathematics)","score":0.5921130180358887},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.5274947881698608},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5040730237960815},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.49479883909225464},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3969542980194092},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3857424855232239},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.35546809434890747},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08172699809074402},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06924259662628174}],"concepts":[{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.7988390922546387},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.797357439994812},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7864886522293091},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6425200700759888},{"id":"https://openalex.org/C122041747","wikidata":"https://www.wikidata.org/wiki/Q838611","display_name":"Ball (mathematics)","level":2,"score":0.5921130180358887},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.5274947881698608},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5040730237960815},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.49479883909225464},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3969542980194092},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3857424855232239},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35546809434890747},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08172699809074402},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06924259662628174},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1145/3347318.3355517","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3347318.3355517","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings Proceedings of the 2nd International Workshop on Multimedia Content Analysis in Sports","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2007.11876","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.11876","pdf_url":"https://arxiv.org/pdf/2007.11876","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"pmh:oai:dial.uclouvain.be:boreal:219159","is_oa":true,"landing_page_url":"http://hdl.handle.net/2078.1/219159","pdf_url":null,"source":{"id":"https://openalex.org/S4306401902","display_name":"Digital Access to Libraries (Universit\u00e9 catholique de Louvain (UCL), l'Universit\u00e9 de Namur (UNamur) and the Universit\u00e9 Saint-Louis (USL-B))","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I95674353","host_organization_name":"UCLouvain","host_organization_lineage":["https://openalex.org/I95674353"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Proceedings of ACM Multimedia 2019, Vol. 1, no.1, p. 8 (2019)","raw_type":"info:eu-repo/semantics/conferenceObject"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2007.11876","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2007.11876","pdf_url":"https://arxiv.org/pdf/2007.11876","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"display_name":"Sustainable cities and communities","score":0.4000000059604645,"id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":46,"referenced_works":["https://openalex.org/W1499901540","https://openalex.org/W1861492603","https://openalex.org/W1976897890","https://openalex.org/W1996811594","https://openalex.org/W1997436935","https://openalex.org/W2023350416","https://openalex.org/W2068277723","https://openalex.org/W2070757849","https://openalex.org/W2095193483","https://openalex.org/W2103290417","https://openalex.org/W2109139211","https://openalex.org/W2111930625","https://openalex.org/W2114924283","https://openalex.org/W2116227586","https://openalex.org/W2122217536","https://openalex.org/W2147677681","https://openalex.org/W2149839055","https://openalex.org/W2158511058","https://openalex.org/W2169837433","https://openalex.org/W2177258564","https://openalex.org/W2243825728","https://openalex.org/W2436270489","https://openalex.org/W2515385951","https://openalex.org/W2523103428","https://openalex.org/W2571453198","https://openalex.org/W2607170611","https://openalex.org/W2609286783","https://openalex.org/W2630837129","https://openalex.org/W2767065048","https://openalex.org/W2803097213","https://openalex.org/W2884370868","https://openalex.org/W2886934227","https://openalex.org/W2887976372","https://openalex.org/W2890957154","https://openalex.org/W2910489404","https://openalex.org/W2919115771","https://openalex.org/W2952122856","https://openalex.org/W2962965870","https://openalex.org/W2963150697","https://openalex.org/W2963372527","https://openalex.org/W2963623257","https://openalex.org/W2963785012","https://openalex.org/W2963800917","https://openalex.org/W2964217532","https://openalex.org/W4289751823","https://openalex.org/W6600577311"],"related_works":["https://openalex.org/W2055243143","https://openalex.org/W4379231730","https://openalex.org/W1986418932","https://openalex.org/W2357796999","https://openalex.org/W4321636575","https://openalex.org/W2588198209","https://openalex.org/W1909006023","https://openalex.org/W4205824991","https://openalex.org/W2741131631","https://openalex.org/W1522196789"],"abstract_inverted_index":{"This":[0],"paper":[1],"considers":[2],"the":[3,7,14,20,33,42,58,61,80,99,109],"task":[4,47],"of":[5,57,68],"detecting":[6],"ball":[8,21,59],"from":[9],"a":[10,37,45,66,84,96],"single":[11],"viewpoint":[12],"in":[13,76],"challenging":[15],"but":[16],"common":[17],"case":[18],"where":[19],"interacts":[22],"frequently":[23],"with":[24,30,65],"players":[25],"while":[26],"being":[27],"poorly":[28],"contrasted":[29],"respect":[31],"to":[32],"background.":[34],"We":[35,87],"propose":[36],"novel":[38],"approach":[39],"by":[40,49,83],"formulating":[41],"problem":[43],"as":[44],"segmentation":[46],"solved":[48],"an":[50,103],"efficient":[51],"CNN":[52],"architecture.":[53],"To":[54],"take":[55],"advantage":[56],"dynamics,":[60],"network":[62],"is":[63,115],"fed":[64],"pair":[67],"consecutive":[69],"images.":[70],"Our":[71],"inference":[72],"model":[73],"can":[74],"run":[75],"real":[77],"time":[78],"without":[79],"delay":[81],"induced":[82],"temporal":[85],"analysis.":[86],"also":[88],"show":[89],"that":[90],"test-time":[91],"data":[92],"augmentation":[93],"allows":[94],"for":[95],"significant":[97],"increase":[98],"detection":[100],"accuracy.":[101],"As":[102],"additional":[104],"contribution,":[105],"we":[106],"publicly":[107],"release":[108],"dataset":[110],"on":[111],"which":[112],"this":[113],"work":[114],"based.":[116]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":4},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":1}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}