{"id":"https://openalex.org/W4403792095","doi":"https://doi.org/10.1145/3664647.3680774","title":"Explicit Granularity and Implicit Scale Correspondence Learning for Point-Supervised Video Moment Localization","display_name":"Explicit Granularity and Implicit Scale Correspondence Learning for Point-Supervised Video Moment Localization","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403792095","doi":"https://doi.org/10.1145/3664647.3680774"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3680774","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680774","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100366746","display_name":"Kun Wang","orcid":"https://orcid.org/0009-0008-4856-8806"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kun Wang","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0008-4856-8806","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Hao Liu","orcid":"https://orcid.org/0009-0003-1026-4499"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Liu","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0003-1026-4499","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5036118073","display_name":"Lu Jie","orcid":"https://orcid.org/0009-0005-6895-3558"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lirong Jie","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0005-6895-3558","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Zixu Li","orcid":"https://orcid.org/0009-0001-5136-159X"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixu Li","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0009-0001-5136-159X","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101875643","display_name":"Yupeng Hu","orcid":"https://orcid.org/0000-0002-5653-8286"},"institutions":[{"id":"https://openalex.org/I154099455","display_name":"Shandong University","ror":"https://ror.org/0207yh398","country_code":"CN","type":"education","lineage":["https://openalex.org/I154099455"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yupeng Hu","raw_affiliation_strings":["Shandong University, Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-5653-8286","affiliations":[{"raw_affiliation_string":"Shandong University, Jinan, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5038612499","display_name":"Liqiang Nie","orcid":"https://orcid.org/0000-0003-1476-0273"},"institutions":[{"id":"https://openalex.org/I204983213","display_name":"Harbin Institute of Technology","ror":"https://ror.org/01yqg2h08","country_code":"CN","type":"education","lineage":["https://openalex.org/I204983213"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liqiang Nie","raw_affiliation_strings":["Harbin Institute of Technology, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-1476-0273","affiliations":[{"raw_affiliation_string":"Harbin Institute of Technology, Shenzhen, China","institution_ids":["https://openalex.org/I204983213"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.1873,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.8920759,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"9214","last_page":"9223"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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"}},"topics":[{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.996999979019165,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9955000281333923,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/granularity","display_name":"Granularity","score":0.8685712218284607},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.647278904914856},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.6266055703163147},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5829306840896606},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5750136375427246},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.5495511293411255},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3926818072795868},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.38645249605178833},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2176910638809204},{"id":"https://openalex.org/keywords/geometry","display_name":"Geometry","score":0.10550928115844727},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.0812341570854187},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.059540748596191406}],"concepts":[{"id":"https://openalex.org/C177774035","wikidata":"https://www.wikidata.org/wiki/Q1246948","display_name":"Granularity","level":2,"score":0.8685712218284607},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.647278904914856},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.6266055703163147},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5829306840896606},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5750136375427246},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.5495511293411255},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3926818072795868},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.38645249605178833},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2176910638809204},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.10550928115844727},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.0812341570854187},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.059540748596191406},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C74650414","wikidata":"https://www.wikidata.org/wiki/Q11397","display_name":"Classical mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3680774","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680774","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":52,"referenced_works":["https://openalex.org/W611457968","https://openalex.org/W1522734439","https://openalex.org/W1942126453","https://openalex.org/W2111078031","https://openalex.org/W2250539671","https://openalex.org/W2337252826","https://openalex.org/W2798354744","https://openalex.org/W2963017553","https://openalex.org/W2963393391","https://openalex.org/W2963524571","https://openalex.org/W2964089981","https://openalex.org/W2964935470","https://openalex.org/W2981750465","https://openalex.org/W2997429269","https://openalex.org/W2998355566","https://openalex.org/W3035635319","https://openalex.org/W3088744711","https://openalex.org/W3103542727","https://openalex.org/W3135773387","https://openalex.org/W3156861396","https://openalex.org/W3157181916","https://openalex.org/W3167366812","https://openalex.org/W3174026887","https://openalex.org/W3174572181","https://openalex.org/W3189379416","https://openalex.org/W3199871897","https://openalex.org/W3211772574","https://openalex.org/W3212024868","https://openalex.org/W4212774754","https://openalex.org/W4214582399","https://openalex.org/W4214931087","https://openalex.org/W4224314500","https://openalex.org/W4225547367","https://openalex.org/W4283361723","https://openalex.org/W4283814553","https://openalex.org/W4283822025","https://openalex.org/W4295046616","https://openalex.org/W4312121894","https://openalex.org/W4312271977","https://openalex.org/W4312402470","https://openalex.org/W4312583258","https://openalex.org/W4327852044","https://openalex.org/W4385571847","https://openalex.org/W4385573643","https://openalex.org/W4386076225","https://openalex.org/W4386527955","https://openalex.org/W4387968116","https://openalex.org/W4388187692","https://openalex.org/W4390873056","https://openalex.org/W4393149608","https://openalex.org/W4393159035","https://openalex.org/W4396743044"],"related_works":["https://openalex.org/W2931688134","https://openalex.org/W2377919138","https://openalex.org/W2378857091","https://openalex.org/W2999756192","https://openalex.org/W103652678","https://openalex.org/W4226090359","https://openalex.org/W2059697060","https://openalex.org/W936373746","https://openalex.org/W2975817033","https://openalex.org/W4382701072"],"abstract_inverted_index":{"Video":[0],"moment":[1],"localization":[2,18],"(VML)":[3],"aims":[4],"to":[5,28,88,100],"identify":[6,101],"the":[7,12,70,114],"temporal":[8],"boundary":[9],"semantically":[10],"matching":[11],"given":[13],"query.":[14],"Point-supervised":[15],"VML":[16],"balances":[17],"accuracy":[19],"and":[20,31,43,67,81,95,102],"annotation":[21,54],"cost":[22],"but":[23],"is":[24],"still":[25],"immature":[26],"due":[27],"granularity":[29,85],"alignment":[30,87],"scale":[32,97,105],"perception":[33],"issues.":[34],"To":[35],"this":[36],"end,":[37],"we":[38],"propose":[39],"a":[40,96],"Semantic":[41],"Granularity":[42],"Scale":[44],"Correspondence":[45],"Integration":[46],"(SG-SCI)":[47],"framework":[48],"aimed":[49],"at":[50],"leveraging":[51],"limited":[52],"single-frame":[53],"for":[55],"correspondence":[56,86,98],"learning.":[57],"It":[58],"explicitly":[59],"models":[60],"semantic":[61,72,104],"relations":[62],"of":[63,78,117],"different":[64],"feature":[65,76],"granularities":[66,80],"adaptively":[68],"mines":[69],"implicit":[71],"scale,":[73],"thereby":[74],"enhancing":[75],"representations":[77],"varying":[79],"scales.":[82],"SG-SCI":[83],"uses":[84],"align":[89],"semantics":[90],"via":[91],"latent":[92],"prior":[93],"knowledge":[94],"learning":[99],"address":[103],"differences.":[106],"Extensive":[107],"experiments":[108],"on":[109],"benchmark":[110],"datasets":[111],"have":[112],"demonstrated":[113],"promising":[115],"performance":[116],"our":[118],"model":[119],"over":[120],"several":[121],"state-of-the-art":[122],"competitors.":[123]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":6}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}