{"id":"https://openalex.org/W4285146284","doi":"https://doi.org/10.1109/tmm.2022.3174344","title":"Multi-Dimensional Attention With Similarity Constraint for Weakly-Supervised Temporal Action Localization","display_name":"Multi-Dimensional Attention With Similarity Constraint for Weakly-Supervised Temporal Action Localization","publication_year":2022,"publication_date":"2022-05-11","ids":{"openalex":"https://openalex.org/W4285146284","doi":"https://doi.org/10.1109/tmm.2022.3174344"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2022.3174344","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3174344","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5103077319","display_name":"Zhengyan Chen","orcid":"https://orcid.org/0000-0002-5044-2400"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhengyan Chen","raw_affiliation_strings":["Key Laboratory of Machine Perception and Shenzhen Graduate School, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception and Shenzhen Graduate School, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100410326","display_name":"Hong Liu","orcid":"https://orcid.org/0000-0002-7498-6541"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hong Liu","raw_affiliation_strings":["Key Laboratory of Machine Perception and Shenzhen Graduate School, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception and Shenzhen Graduate School, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100437396","display_name":"Linlin Zhang","orcid":"https://orcid.org/0000-0003-0966-9096"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Linlin Zhang","raw_affiliation_strings":["Key Laboratory of Machine Perception and Shenzhen Graduate School, Peking University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Machine Perception and Shenzhen Graduate School, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100716299","display_name":"Xin Liao","orcid":null},"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":"Xin Liao","raw_affiliation_strings":["College of Computer Science and Electronic Engineering, Hunan University, Changsha, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science and Electronic Engineering, Hunan University, Changsha, China","institution_ids":["https://openalex.org/I16609230"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5103077319"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.5285,"has_fulltext":false,"cited_by_count":16,"citation_normalized_percentile":{"value":0.83767829,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":"25","issue":null,"first_page":"4349","last_page":"4360"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":1.0,"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":1.0,"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":0.9933000206947327,"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":0.9926999807357788,"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/discriminative-model","display_name":"Discriminative model","score":0.8030915260314941},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7455964684486389},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7143223881721497},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5600205063819885},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.550557553768158},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.5459720492362976},{"id":"https://openalex.org/keywords/constraint","display_name":"Constraint (computer-aided design)","score":0.5423882603645325},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5291274785995483},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4830206334590912},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.46266651153564453},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3556990623474121},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.17541873455047607},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12250053882598877}],"concepts":[{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.8030915260314941},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7455964684486389},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7143223881721497},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5600205063819885},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.550557553768158},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.5459720492362976},{"id":"https://openalex.org/C2776036281","wikidata":"https://www.wikidata.org/wiki/Q48769818","display_name":"Constraint (computer-aided design)","level":2,"score":0.5423882603645325},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5291274785995483},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4830206334590912},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.46266651153564453},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3556990623474121},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.17541873455047607},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12250053882598877},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2022.3174344","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2022.3174344","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.7300000190734863,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G2682340759","display_name":null,"funder_award_id":"62073004","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4054341898","display_name":null,"funder_award_id":"61972142","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G4117658732","display_name":null,"funder_award_id":"JCYJ20200109140410340","funder_id":"https://openalex.org/F4320329791","funder_display_name":"Shenzhen Fundamental Research Program"},{"id":"https://openalex.org/G5548261648","display_name":null,"funder_award_id":"GXWD20201231165807007-20200807164903001","funder_id":"https://openalex.org/F4320329791","funder_display_name":"Shenzhen Fundamental Research Program"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320329791","display_name":"Shenzhen Fundamental Research Program","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":69,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W846669277","https://openalex.org/W1522734439","https://openalex.org/W1578985305","https://openalex.org/W1839676122","https://openalex.org/W1927052826","https://openalex.org/W1947481528","https://openalex.org/W2105101328","https://openalex.org/W2336403884","https://openalex.org/W2342662179","https://openalex.org/W2593722617","https://openalex.org/W2597958930","https://openalex.org/W2604113307","https://openalex.org/W2788945907","https://openalex.org/W2804867909","https://openalex.org/W2883429621","https://openalex.org/W2884293275","https://openalex.org/W2884969173","https://openalex.org/W2895240652","https://openalex.org/W2948229620","https://openalex.org/W2950534130","https://openalex.org/W2952435096","https://openalex.org/W2961553857","https://openalex.org/W2962677524","https://openalex.org/W2962709777","https://openalex.org/W2962876901","https://openalex.org/W2962934715","https://openalex.org/W2963045696","https://openalex.org/W2963155035","https://openalex.org/W2963400312","https://openalex.org/W2963524571","https://openalex.org/W2964036161","https://openalex.org/W2964214371","https://openalex.org/W2964216549","https://openalex.org/W2964274041","https://openalex.org/W2974686944","https://openalex.org/W2976669726","https://openalex.org/W2976863923","https://openalex.org/W2983918066","https://openalex.org/W2984478308","https://openalex.org/W2984619425","https://openalex.org/W2986407524","https://openalex.org/W2988098865","https://openalex.org/W2989042503","https://openalex.org/W2996173702","https://openalex.org/W2997706915","https://openalex.org/W2998601171","https://openalex.org/W2998702159","https://openalex.org/W3014545861","https://openalex.org/W3033595049","https://openalex.org/W3034623254","https://openalex.org/W3092976396","https://openalex.org/W3095669214","https://openalex.org/W3097664769","https://openalex.org/W3109715102","https://openalex.org/W3121052081","https://openalex.org/W3173212682","https://openalex.org/W3173698268","https://openalex.org/W3173874725","https://openalex.org/W3176444885","https://openalex.org/W3176641851","https://openalex.org/W3178036208","https://openalex.org/W3182120198","https://openalex.org/W6631190155","https://openalex.org/W6682864246","https://openalex.org/W6739901393","https://openalex.org/W6760239191","https://openalex.org/W6766978945","https://openalex.org/W6790320674"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"Weakly-supervised":[0],"temporal":[1,33,91],"action":[2,80,98,110,141,158,163,177],"localization":[3],"(WTAL)":[4],"is":[5,18,27],"a":[6,65,134],"challenging":[7],"task":[8],"in":[9,13,77,144],"understanding":[10],"untrimmed":[11],"videos,":[12],"which":[14,147],"no":[15],"frame-wise":[16],"annotation":[17],"provided":[19],"during":[20,127],"training,":[21],"only":[22],"the":[23,50,55,105,140,149,161,193,197],"video-level":[24],"category":[25],"label":[26],"available.":[28],"Current":[29],"methods":[30],"mainly":[31],"adopt":[32],"attention":[34,72,92,102,115],"branches":[35],"to":[36,70,138,151,159,175],"conduct":[37],"foreground-background":[38],"separation":[39],"with":[40,168,180,206],"RGB":[41,118],"and":[42,54,112,119,187,202],"optical":[43],"flow":[44,120],"features":[45,53],"simply":[46],"concatenated,":[47],"regardless":[48],"of":[49,156],"discriminative":[51,154],"spacial":[52],"complementarity":[56],"between":[57],"different":[58],"modalities.":[59],"In":[60,130],"this":[61],"work,":[62],"we":[63,132],"propose":[64],"Multi-Dimensional":[66],"Attention":[67],"(MDA)":[68],"method":[69,195],"explore":[71],"mechanism":[73],"across":[74],"three":[75],"dimensions":[76],"weakly":[78],"supervised":[79],"localization,":[81],"<italic":[82,86],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[83,87],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">i</i>":[84],".":[85],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">e</i>":[88],".,":[89],"1)":[90],"that":[93,103,116,192],"focuses":[94],"on":[95,124,185],"segments":[96],"containing":[97],"instances,":[99],"2)":[100],"channel":[101],"discovers":[104],"most":[106],"relevant":[107],"cues":[108],"for":[109],"description,":[111],"3)":[113],"modal":[114],"fuses":[117],"information":[121],"adaptively":[122],"based":[123],"feature":[125,145],"magnitudes":[126],"background":[128],"modeling.":[129],"addition,":[131],"introduce":[133],"similarity":[135,169],"constraint":[136],"loss":[137],"refine":[139],"segment":[142],"representation":[143],"space,":[146],"helps":[148],"network":[150],"detect":[152],"less":[153],"frames":[155],"an":[157],"capture":[160],"full":[162],"boundaries.":[164],"The":[165],"proposed":[166,194],"MDA":[167],"constraints":[170],"can":[171],"be":[172],"easily":[173],"applied":[174],"existing":[176],"detection":[178],"frameworks":[179],"few":[181],"parameters.":[182],"Extensive":[183],"experiments":[184],"THUMOS\u201914":[186],"ActivityNet":[188],"v1.2":[189],"datasets":[190],"show":[191],"outperforms":[196],"current":[198],"state-of-the-art":[199],"WTAL":[200],"approaches,":[201],"achieves":[203],"comparable":[204],"results":[205],"some":[207],"advanced":[208],"fully-supervised":[209],"methods.":[210]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":5},{"year":2023,"cited_by_count":2}],"updated_date":"2026-03-27T14:29:43.386196","created_date":"2025-10-10T00:00:00"}