{"id":"https://openalex.org/W3093206850","doi":"https://doi.org/10.1145/3394171.3413841","title":"Adversarial Video Moment Retrieval by Jointly Modeling Ranking and Localization","display_name":"Adversarial Video Moment Retrieval by Jointly Modeling Ranking and Localization","publication_year":2020,"publication_date":"2020-10-12","ids":{"openalex":"https://openalex.org/W3093206850","doi":"https://doi.org/10.1145/3394171.3413841","mag":"3093206850"},"language":"en","primary_location":{"id":"doi:10.1145/3394171.3413841","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413841","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th 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/A5078164599","display_name":"Da Cao","orcid":"https://orcid.org/0000-0002-2611-2559"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Da Cao","raw_affiliation_strings":["Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017828551","display_name":"Yawen Zeng","orcid":"https://orcid.org/0000-0003-1908-1157"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yawen Zeng","raw_affiliation_strings":["Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069000781","display_name":"Xiaochi Wei","orcid":"https://orcid.org/0000-0003-4359-4024"},"institutions":[{"id":"https://openalex.org/I98301712","display_name":"Baidu (China)","ror":"https://ror.org/03vs3wt56","country_code":"CN","type":"company","lineage":["https://openalex.org/I98301712"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaochi Wei","raw_affiliation_strings":["Baidu Inc., Beijing, China"],"affiliations":[{"raw_affiliation_string":"Baidu Inc., Beijing, China","institution_ids":["https://openalex.org/I98301712"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5038612499","display_name":"Liqiang Nie","orcid":"https://orcid.org/0000-0003-1476-0273"},"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":"Liqiang Nie","raw_affiliation_strings":["Shandong University, Qingdao, China"],"affiliations":[{"raw_affiliation_string":"Shandong University, Qingdao, China","institution_ids":["https://openalex.org/I154099455"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5051332325","display_name":"Richang Hong","orcid":"https://orcid.org/0000-0001-5461-3986"},"institutions":[{"id":"https://openalex.org/I16365422","display_name":"Hefei University of Technology","ror":"https://ror.org/02czkny70","country_code":"CN","type":"education","lineage":["https://openalex.org/I16365422"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Richang Hong","raw_affiliation_strings":["Hefei University of Technology, Hefei, China"],"affiliations":[{"raw_affiliation_string":"Hefei University of Technology, Hefei, China","institution_ids":["https://openalex.org/I16365422"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5035491991","display_name":"Zheng Qin","orcid":"https://orcid.org/0000-0003-0877-3887"},"institutions":[{"id":"https://openalex.org/I16609230","display_name":"Hunan University","ror":"https://ror.org/05htk5m33","country_code":"CN","type":"education","lineage":["https://openalex.org/I16609230"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Qin","raw_affiliation_strings":["Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5078164599"],"corresponding_institution_ids":["https://openalex.org/I16609230"],"apc_list":null,"apc_paid":null,"fwci":2.7355,"has_fulltext":false,"cited_by_count":36,"citation_normalized_percentile":{"value":0.92081737,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"898","last_page":"906"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9998000264167786,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9986000061035156,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.9983000159263611,"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/computer-science","display_name":"Computer science","score":0.7913563251495361},{"id":"https://openalex.org/keywords/moment","display_name":"Moment (physics)","score":0.7022878527641296},{"id":"https://openalex.org/keywords/discriminator","display_name":"Discriminator","score":0.6906843781471252},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.6763802766799927},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5635829567909241},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5368417501449585},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.5129813551902771},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.5055291652679443},{"id":"https://openalex.org/keywords/pairwise-comparison","display_name":"Pairwise comparison","score":0.505352795124054},{"id":"https://openalex.org/keywords/rank","display_name":"Rank (graph theory)","score":0.4758429527282715},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4373353123664856},{"id":"https://openalex.org/keywords/adversarial-system","display_name":"Adversarial system","score":0.42672866582870483},{"id":"https://openalex.org/keywords/power","display_name":"Power (physics)","score":0.09614866971969604},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09562832117080688}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7913563251495361},{"id":"https://openalex.org/C179254644","wikidata":"https://www.wikidata.org/wiki/Q13222844","display_name":"Moment (physics)","level":2,"score":0.7022878527641296},{"id":"https://openalex.org/C2779803651","wikidata":"https://www.wikidata.org/wiki/Q5282088","display_name":"Discriminator","level":3,"score":0.6906843781471252},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.6763802766799927},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5635829567909241},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5368417501449585},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.5129813551902771},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.5055291652679443},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.505352795124054},{"id":"https://openalex.org/C164226766","wikidata":"https://www.wikidata.org/wiki/Q7293202","display_name":"Rank (graph theory)","level":2,"score":0.4758429527282715},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4373353123664856},{"id":"https://openalex.org/C37736160","wikidata":"https://www.wikidata.org/wiki/Q1801315","display_name":"Adversarial system","level":2,"score":0.42672866582870483},{"id":"https://openalex.org/C163258240","wikidata":"https://www.wikidata.org/wiki/Q25342","display_name":"Power (physics)","level":2,"score":0.09614866971969604},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09562832117080688},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3394171.3413841","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3394171.3413841","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 28th ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G431648992","display_name":null,"funder_award_id":"61802121","funder_id":"https://openalex.org/F4320327720","funder_display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320327720","display_name":"Foundation for Innovative Research Groups of the National Natural Science Foundation of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W1923404803","https://openalex.org/W1942126453","https://openalex.org/W2111078031","https://openalex.org/W2194775991","https://openalex.org/W2337252826","https://openalex.org/W2619206542","https://openalex.org/W2737041163","https://openalex.org/W2765440071","https://openalex.org/W2767170755","https://openalex.org/W2798354744","https://openalex.org/W2798538558","https://openalex.org/W2798868970","https://openalex.org/W2894280539","https://openalex.org/W2897152025","https://openalex.org/W2897628926","https://openalex.org/W2903901502","https://openalex.org/W2913696151","https://openalex.org/W2915049075","https://openalex.org/W2948958195","https://openalex.org/W2951748488","https://openalex.org/W2962869524","https://openalex.org/W2963017553","https://openalex.org/W2963095467","https://openalex.org/W2963735856","https://openalex.org/W2964089981","https://openalex.org/W2964232540","https://openalex.org/W2966799427","https://openalex.org/W2969689322","https://openalex.org/W2981352610","https://openalex.org/W2981404046","https://openalex.org/W2981433975","https://openalex.org/W2981557889","https://openalex.org/W2981750465","https://openalex.org/W3011809564","https://openalex.org/W3101023724","https://openalex.org/W3101429639","https://openalex.org/W3106445281"],"related_works":["https://openalex.org/W4293202849","https://openalex.org/W1980965563","https://openalex.org/W1489300767","https://openalex.org/W2387995142","https://openalex.org/W2995777218","https://openalex.org/W2011472225","https://openalex.org/W3000057026","https://openalex.org/W3048565508","https://openalex.org/W3163984363","https://openalex.org/W3160516639"],"abstract_inverted_index":{"Retrieving":[0],"video":[1,6,34,43,47,91,109,138,154,184,188],"moments":[2,155],"from":[3],"an":[4,114],"untrimmed":[5],"given":[7],"a":[8,15,65,84,124,130,134,141,148],"natural":[9],"language":[10],"as":[11,113,129,147],"the":[12,90,96,108,152,157,161,164,170,180,200],"query":[13],"is":[14,76,105,127,145,175],"challenging":[16],"task":[17,112],"in":[18,169],"both":[19,183],"academia":[20],"and":[21,46,62,72,156,163,187,202],"industry.":[22],"Although":[23],"much":[24],"effort":[25],"has":[26],"been":[27],"made":[28],"to":[29,40,54,59,68,87,106,132,150,177],"address":[30],"this":[31,80],"issue,":[32],"traditional":[33],"moment":[35,44,48,92,110,185,189],"ranking":[36,61,143,186],"methods":[37],"are":[38,51,166],"unable":[39],"generate":[41],"reasonable":[42],"candidates":[45],"localization":[49,63],"approaches":[50],"not":[52],"applicable":[53],"large-scale":[55],"retrieval":[56,93,111],"scenario.":[57],"How":[58],"combine":[60],"into":[64],"unified":[66],"framework":[67],"overcome":[69],"their":[70],"drawbacks":[71],"reinforce":[73],"each":[74],"other":[75],"rarely":[77],"considered.":[78],"Toward":[79],"end,":[81],"we":[82],"contribute":[83],"novel":[85],"solution":[86,104],"thoroughly":[88],"investigate":[89],"issue":[94],"under":[95],"adversarial":[97,115,171],"learning":[98,116,126,172],"paradigm.":[99],"The":[100],"key":[101],"of":[102,136,182,204],"our":[103,205],"formulate":[107],"problem":[117],"with":[118],"two":[119,194],"tightly":[120],"connected":[121],"components.":[122],"Specifically,":[123],"reinforcement":[125],"employed":[128],"generator":[131,162],"produce":[133],"set":[135],"possible":[137],"moments.":[139],"Meanwhile,":[140],"pairwise":[142],"model":[144],"utilized":[146],"discriminator":[149,165],"rank":[151],"generated":[153],"ground":[158],"truth.":[159],"Finally,":[160],"mutually":[167],"reinforced":[168],"framework,":[173],"which":[174],"able":[176],"jointly":[178],"optimize":[179],"performance":[181],"localization.":[190],"Extensive":[191],"experiments":[192],"on":[193],"well-known":[195],"datasets":[196],"have":[197],"well":[198],"verified":[199],"effectiveness":[201],"rationality":[203],"proposed":[206],"solution.":[207]},"counts_by_year":[{"year":2025,"cited_by_count":5},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":11},{"year":2021,"cited_by_count":9}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
