{"id":"https://openalex.org/W4293518083","doi":"https://doi.org/10.1109/icme52920.2022.9860007","title":"Mr.CAN: Class-Aware Network with Multi-Relations for Temporal Action Detection","display_name":"Mr.CAN: Class-Aware Network with Multi-Relations for Temporal Action Detection","publication_year":2022,"publication_date":"2022-07-18","ids":{"openalex":"https://openalex.org/W4293518083","doi":"https://doi.org/10.1109/icme52920.2022.9860007"},"language":"en","primary_location":{"id":"doi:10.1109/icme52920.2022.9860007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9860007","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5101989821","display_name":"Dongqi Wang","orcid":"https://orcid.org/0000-0001-6046-7153"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongqi Wang","raw_affiliation_strings":["Shanghai Jiao Tong University,Department of Automation,Shanghai,China","Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5039486936","display_name":"Zixuan Zhao","orcid":null},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zixuan Zhao","raw_affiliation_strings":["Shanghai Jiao Tong University,Department of Automation,Shanghai,China","Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100440525","display_name":"Xu Zhao","orcid":"https://orcid.org/0000-0002-8176-623X"},"institutions":[{"id":"https://openalex.org/I183067930","display_name":"Shanghai Jiao Tong University","ror":"https://ror.org/0220qvk04","country_code":"CN","type":"education","lineage":["https://openalex.org/I183067930"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xu Zhao","raw_affiliation_strings":["Shanghai Jiao Tong University,Department of Automation,Shanghai,China","Department of Automation, Shanghai Jiao Tong University, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shanghai Jiao Tong University,Department of Automation,Shanghai,China","institution_ids":["https://openalex.org/I183067930"]},{"raw_affiliation_string":"Department of Automation, Shanghai Jiao Tong University, Shanghai, China","institution_ids":["https://openalex.org/I183067930"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I183067930"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"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/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"}},{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9948999881744385,"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/computer-science","display_name":"Computer science","score":0.8410659432411194},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.7072558403015137},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7071439027786255},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.6533796787261963},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5520749092102051},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4523700773715973},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41638290882110596},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.41400110721588135},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.37594854831695557},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3303844928741455},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3293190598487854},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.08580926060676575}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8410659432411194},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.7072558403015137},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7071439027786255},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.6533796787261963},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5520749092102051},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4523700773715973},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41638290882110596},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.41400110721588135},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.37594854831695557},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3303844928741455},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3293190598487854},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.08580926060676575},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme52920.2022.9860007","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme52920.2022.9860007","pdf_url":null,"source":{"id":"https://openalex.org/S4363607799","display_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G768824778","display_name":null,"funder_award_id":"62176156","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":29,"referenced_works":["https://openalex.org/W1927052826","https://openalex.org/W2156303437","https://openalex.org/W2486996822","https://openalex.org/W2604113307","https://openalex.org/W2948229620","https://openalex.org/W2962677524","https://openalex.org/W2963524571","https://openalex.org/W2964121718","https://openalex.org/W2983918066","https://openalex.org/W2986407524","https://openalex.org/W2997706915","https://openalex.org/W3034623254","https://openalex.org/W3106041614","https://openalex.org/W3110337427","https://openalex.org/W3110589170","https://openalex.org/W3128626728","https://openalex.org/W3133570661","https://openalex.org/W3174569083","https://openalex.org/W3176444885","https://openalex.org/W3176641851","https://openalex.org/W3208474254","https://openalex.org/W4230270698","https://openalex.org/W4385245566","https://openalex.org/W6682864246","https://openalex.org/W6722654596","https://openalex.org/W6739901393","https://openalex.org/W6751389191","https://openalex.org/W6783470697","https://openalex.org/W6791571585"],"related_works":["https://openalex.org/W4234874385","https://openalex.org/W2323648130","https://openalex.org/W2157140558","https://openalex.org/W2378782423","https://openalex.org/W2388988621","https://openalex.org/W2357797405","https://openalex.org/W2366623913","https://openalex.org/W2045408812","https://openalex.org/W2354233396","https://openalex.org/W2888033806"],"abstract_inverted_index":{"Recognizing":[0],"action":[1,21,74],"patterns":[2],"and":[3,19,52,80,103,131,145],"exploring":[4],"multiple":[5],"relations":[6,54,105],"are":[7,110],"vital":[8],"for":[9],"Temporal":[10],"Action":[11],"Detection":[12],"(TAD)":[13],"task,":[14],"which":[15],"aims":[16],"at":[17],"locating":[18],"classifying":[20],"segments":[22,57],"in":[23],"untrimmed":[24],"videos.":[25],"However,":[26],"most":[27],"existing":[28,166],"methods":[29,130],"attempt":[30],"to":[31,36,63,87,100,141,148,162],"build":[32],"a":[33,83],"general":[34],"model":[35],"handle":[37],"diverse":[38],"actions,":[39],"ignoring":[40],"the":[41,48,136,154],"huge":[42],"difference":[43],"between":[44,55],"various":[45],"classes.":[46],"Besides,":[47],"exploration":[49],"of":[50],"temporal":[51,102],"semantic":[53,104],"different":[56,73],"remains":[58],"an":[59,92],"ongoing":[60],"challenge":[61],"due":[62],"complex":[64],"video":[65],"content.":[66],"In":[67,118],"this":[68],"paper,":[69],"we":[70],"contend":[71],"that":[72],"classes":[75],"should":[76],"be":[77,160],"processed":[78],"differently":[79],"thus":[81],"design":[82],"new":[84],"Class-Aware":[85,113],"Mechanism":[86],"achieve":[88],"accurate":[89],"detection.":[90],"Moreover,":[91],"effective":[93],"module":[94],"named":[95],"Multi-relations":[96,116,156],"Builder":[97,157],"is":[98],"proposed":[99],"establish":[101],"simultaneously.":[106],"These":[107],"two":[108,123],"modules":[109],"integrated":[111],"as":[112],"Network":[114],"with":[115],"(MrCAN).":[117],"comprehensive":[119],"experiments":[120],"conducted":[121],"on":[122,143,150],"benchmarks,":[124],"it":[125],"out-performs":[126],"all":[127],"other":[128,165],"current":[129],"achieves":[132],"state-of-the-art":[133],"performance,":[134],"improving":[135],"average":[137],"mAP":[138],"from":[139,146],"45.78%":[140],"48.98%":[142],"THUMOS-14":[144],"35.52%":[147],"35.87%":[149],"ActivityNet-1.3":[151],"respectively.":[152],"Furthermore,":[153],"well-designed":[155],"can":[158],"also":[159],"used":[161],"boost":[163],"some":[164],"methods.":[167]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
