{"id":"https://openalex.org/W4403780787","doi":"https://doi.org/10.1145/3664647.3681200","title":"Saliency-Guided Fine-Grained Temporal Mask Learning for Few-Shot Action Recognition","display_name":"Saliency-Guided Fine-Grained Temporal Mask Learning for Few-Shot Action Recognition","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403780787","doi":"https://doi.org/10.1145/3664647.3681200"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3681200","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681200","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/A5059107623","display_name":"Shuo Zheng","orcid":null},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shuo Zheng","raw_affiliation_strings":["Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5053561781","display_name":"Yuanjie Dang","orcid":"https://orcid.org/0000-0002-8302-1338"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanjie Dang","raw_affiliation_strings":["Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100659434","display_name":"Peng Chen","orcid":"https://orcid.org/0000-0001-6122-0574"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peng Chen","raw_affiliation_strings":["Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003099788","display_name":"Ruohong Huan","orcid":"https://orcid.org/0000-0003-2555-343X"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ruohong Huan","raw_affiliation_strings":["Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078620613","display_name":"Dongdong Zhao","orcid":"https://orcid.org/0000-0001-6032-5083"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongdong Zhao","raw_affiliation_strings":["Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001531117","display_name":"Ronghua Liang","orcid":"https://orcid.org/0000-0003-2077-9608"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ronghua Liang","raw_affiliation_strings":["Zhejiang University of Technology, Hangzhou, China"],"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology, Hangzhou, China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5059107623"],"corresponding_institution_ids":["https://openalex.org/I55712492"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18453691,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1024","last_page":"1033"},"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":0.9969000220298767,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9958999752998352,"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":0.7311912775039673},{"id":"https://openalex.org/keywords/shot","display_name":"Shot (pellet)","score":0.6147825121879578},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5723661184310913},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5338861346244812},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.5118133425712585},{"id":"https://openalex.org/keywords/one-shot","display_name":"One shot","score":0.4698958098888397},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4362230598926544},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3679901957511902},{"id":"https://openalex.org/keywords/materials-science","display_name":"Materials science","score":0.09651774168014526},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.0728711485862732},{"id":"https://openalex.org/keywords/class","display_name":"Class (philosophy)","score":0.06992268562316895},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.06439641118049622}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7311912775039673},{"id":"https://openalex.org/C2778344882","wikidata":"https://www.wikidata.org/wiki/Q278938","display_name":"Shot (pellet)","level":2,"score":0.6147825121879578},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5723661184310913},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5338861346244812},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.5118133425712585},{"id":"https://openalex.org/C2992734406","wikidata":"https://www.wikidata.org/wiki/Q413267","display_name":"One shot","level":2,"score":0.4698958098888397},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4362230598926544},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3679901957511902},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.09651774168014526},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0728711485862732},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.06992268562316895},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.06439641118049622},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C191897082","wikidata":"https://www.wikidata.org/wiki/Q11467","display_name":"Metallurgy","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3681200","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3681200","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W569478347","https://openalex.org/W2108598243","https://openalex.org/W2161969291","https://openalex.org/W2194775991","https://openalex.org/W2618799552","https://openalex.org/W2625366777","https://openalex.org/W2894873912","https://openalex.org/W2963524571","https://openalex.org/W2990503944","https://openalex.org/W3034572008","https://openalex.org/W3035374961","https://openalex.org/W3044220283","https://openalex.org/W3093455342","https://openalex.org/W3095374178","https://openalex.org/W3173271747","https://openalex.org/W3184234949","https://openalex.org/W3192801537","https://openalex.org/W3216270236","https://openalex.org/W4214612132","https://openalex.org/W4221167396","https://openalex.org/W4280490805","https://openalex.org/W4288055492","https://openalex.org/W4295276204","https://openalex.org/W4300860215","https://openalex.org/W4310895557","https://openalex.org/W4312259618","https://openalex.org/W4312312750","https://openalex.org/W4312658081","https://openalex.org/W4312733400","https://openalex.org/W4312804044","https://openalex.org/W4313046672","https://openalex.org/W4313156423","https://openalex.org/W4382465664","https://openalex.org/W4386057769","https://openalex.org/W4386065563","https://openalex.org/W4386065787","https://openalex.org/W4387695265","https://openalex.org/W4390872437","https://openalex.org/W4390874131","https://openalex.org/W6717697761"],"related_works":["https://openalex.org/W2497720472","https://openalex.org/W4292659306","https://openalex.org/W3044321615","https://openalex.org/W2806221744","https://openalex.org/W2326937258","https://openalex.org/W394267150","https://openalex.org/W1576128429","https://openalex.org/W2773965352","https://openalex.org/W4294892107","https://openalex.org/W2357748469"],"abstract_inverted_index":{"Temporal":[0],"relation":[1,20,48,91],"modeling":[2,21,49],"is":[3],"one":[4],"of":[5,9,107,124],"the":[6,28,52,62,70,87,103,121,132,149,155,163],"core":[7],"aspects":[8],"few-shot":[10,53,93,156],"action":[11,30,67,90,94,127,135,151],"recognition.":[12],"Most":[13],"previous":[14],"works":[15],"mainly":[16],"focus":[17],"on":[18,23,176],"temporal":[19,34,47,58,81,88,105,113,141],"based":[22],"coarse-level":[24,46],"actions,":[25],"without":[26],"considering":[27],"atomic":[29,89,126,134,150],"details":[31,68],"and":[32,60,147],"fine-grained":[33,80],"information.":[35,152],"This":[36],"oversight":[37],"represents":[38],"a":[39,78,97,112,139,169],"significant":[40],"limitation":[41],"in":[42,56,69,96],"this":[43],"task.":[44],"Specifically,":[45],"can":[50,158],"make":[51],"models":[54,86],"overfit":[55],"high-discrepancy":[57],"context,":[59],"ignore":[61],"low-discrepancy":[63,133],"but":[64],"high-semantic":[65],"relevance":[66],"video.":[71],"To":[72],"address":[73],"these":[74],"issues,":[75],"we":[76,110,137],"propose":[77],"saliency-guided":[79,140],"mask":[82,114,142],"learning":[83,115],"method":[84],"that":[85],"for":[92,120],"recognition":[95],"finer":[98],"manner.":[99],"First,":[100],"to":[101,117,130,144,168,185],"model":[102],"comprehensive":[104],"relations":[106],"video":[108],"instances,":[109],"design":[111],"architecture":[116],"automatically":[118],"search":[119],"best":[122],"matching":[123],"each":[125],"snippet.":[128],"Next,":[129],"exploit":[131],"features,":[136],"introduce":[138],"module":[143],"adaptively":[145],"locate":[146],"excavate":[148],"After":[153],"that,":[154],"predictions":[157],"be":[159],"obtained":[160],"by":[161],"feeding":[162],"embedded":[164],"rich":[165],"temporal-relation":[166],"features":[167],"common":[170],"feature":[171],"matcher.":[172],"Extensive":[173],"experimental":[174],"results":[175],"standard":[177],"datasets":[178],"demonstrate":[179],"our":[180],"method's":[181],"superior":[182],"performance":[183],"compared":[184],"existing":[186],"state-of-the-art":[187],"methods.":[188]},"counts_by_year":[],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}