{"id":"https://openalex.org/W2892009288","doi":"https://doi.org/10.1109/icip.2018.8451625","title":"Spatiotemporal Pyramid Pooling in 3D Convolutional Neural Networks for Action Recognition","display_name":"Spatiotemporal Pyramid Pooling in 3D Convolutional Neural Networks for Action Recognition","publication_year":2018,"publication_date":"2018-09-07","ids":{"openalex":"https://openalex.org/W2892009288","doi":"https://doi.org/10.1109/icip.2018.8451625","mag":"2892009288"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2018.8451625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451625","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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/A5100349414","display_name":"Cheng Cheng","orcid":"https://orcid.org/0000-0002-8271-3367"},"institutions":[{"id":"https://openalex.org/I4210165038","display_name":"University of Chinese Academy of Sciences","ror":"https://ror.org/05qbk4x57","country_code":"CN","type":"education","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165038"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Cheng Cheng","raw_affiliation_strings":["University of Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Chinese Academy of Sciences","institution_ids":["https://openalex.org/I4210165038"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041894655","display_name":"Pin Lv","orcid":"https://orcid.org/0000-0002-3425-9913"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["CN","TW"],"is_corresponding":false,"raw_author_name":"Pin Lv","raw_affiliation_strings":["Institute of Software Chinese Academy of Sciences (ISCAS)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Software Chinese Academy of Sciences (ISCAS)","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I84653119"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5027552992","display_name":"Bing Su","orcid":"https://orcid.org/0000-0001-8560-1910"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I84653119","display_name":"Academia Sinica","ror":"https://ror.org/05bxb3784","country_code":"TW","type":"facility","lineage":["https://openalex.org/I84653119"]}],"countries":["CN","TW"],"is_corresponding":false,"raw_author_name":"Bing Su","raw_affiliation_strings":["Institute of Software Chinese Academy of Sciences (ISCAS)"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Software Chinese Academy of Sciences (ISCAS)","institution_ids":["https://openalex.org/I4210128818","https://openalex.org/I84653119"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"3468","last_page":"3472"},"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":0.9952999949455261,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.9950000047683716,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.933599054813385},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.8051264882087708},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7943687438964844},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7345355153083801},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6856849789619446},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.6289098858833313},{"id":"https://openalex.org/keywords/action-recognition","display_name":"Action recognition","score":0.5842616558074951},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.5544037818908691},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5282472968101501},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4803125262260437},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4626719653606415},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4578931927680969},{"id":"https://openalex.org/keywords/layer","display_name":"Layer (electronics)","score":0.43865978717803955},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.28082817792892456},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08504962921142578},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.06439286470413208},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.05309036374092102}],"concepts":[{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.933599054813385},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.8051264882087708},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7943687438964844},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7345355153083801},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6856849789619446},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.6289098858833313},{"id":"https://openalex.org/C2987834672","wikidata":"https://www.wikidata.org/wiki/Q4677630","display_name":"Action recognition","level":3,"score":0.5842616558074951},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.5544037818908691},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5282472968101501},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4803125262260437},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4626719653606415},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4578931927680969},{"id":"https://openalex.org/C2779227376","wikidata":"https://www.wikidata.org/wiki/Q6505497","display_name":"Layer (electronics)","level":2,"score":0.43865978717803955},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28082817792892456},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08504962921142578},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.06439286470413208},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.05309036374092102},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","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},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C2777212361","wikidata":"https://www.wikidata.org/wiki/Q5127848","display_name":"Class (philosophy)","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2018.8451625","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2018.8451625","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 25th IEEE International Conference on Image Processing (ICIP)","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":32,"referenced_works":["https://openalex.org/W24089286","https://openalex.org/W787785461","https://openalex.org/W1522734439","https://openalex.org/W1983364832","https://openalex.org/W2068611653","https://openalex.org/W2097117768","https://openalex.org/W2105101328","https://openalex.org/W2109255472","https://openalex.org/W2126579184","https://openalex.org/W2142694332","https://openalex.org/W2151103935","https://openalex.org/W2156303437","https://openalex.org/W2162915993","https://openalex.org/W2179352600","https://openalex.org/W2194775991","https://openalex.org/W2507009361","https://openalex.org/W2519560313","https://openalex.org/W2614884684","https://openalex.org/W2619947201","https://openalex.org/W2736596806","https://openalex.org/W2745519816","https://openalex.org/W2746007478","https://openalex.org/W2963524571","https://openalex.org/W2963616706","https://openalex.org/W6600983433","https://openalex.org/W6622789128","https://openalex.org/W6676338569","https://openalex.org/W6682864246","https://openalex.org/W6724944384","https://openalex.org/W6726623912","https://openalex.org/W6742667445","https://openalex.org/W6955071965"],"related_works":["https://openalex.org/W2953234277","https://openalex.org/W2626256601","https://openalex.org/W2022849497","https://openalex.org/W3081299480","https://openalex.org/W2407190427","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W4390224712","https://openalex.org/W4322096758"],"abstract_inverted_index":{"Deep":[0],"3-dimensional":[1],"convolutional":[2],"networks":[3],"(3D":[4],"ConvNets)":[5],"trained":[6],"on":[7,16,49,105],"large":[8,103],"scale":[9],"video":[10,46,87,108],"datasets":[11],"have":[12],"achieved":[13],"promising":[14],"results":[15],"action":[17],"recognition.":[18],"This":[19],"paper":[20],"improves":[21],"their":[22],"performance":[23],"by":[24,60,101],"taking":[25],"into":[26],"account":[27],"the":[28,35,42,97],"spatiotemporal":[29,36],"pyramid":[30,37],"pooling.":[31],"Specifically,":[32],"we":[33,52],"propose":[34],"pooling":[38],"layer":[39],"to":[40,71],"tackle":[41],"temporal":[43,74],"variations":[44],"of":[45,76,86],"sequences.":[47],"Based":[48],"this":[50],"layer,":[51],"develop":[53],"a":[54,82,102],"new":[55,93],"network":[56,68,94],"architecture,":[57],"called":[58],"STPP-net,":[59],"incorporating":[61],"it":[62],"with":[63],"3D":[64,99],"ConvNets.":[65],"The":[66],"proposed":[67],"is":[69],"robust":[70],"spatial":[72],"and":[73,79,115],"variation":[75],"human":[77],"actions":[78],"can":[80],"generate":[81],"fixed-dimensional":[83],"representation":[84],"regardless":[85],"size/scale.":[88],"We":[89],"show":[90],"that":[91],"our":[92],"architecture":[95],"outperforms":[96],"original":[98],"ConvNets":[100],"margin":[104],"three":[106],"large-scale":[107],"classification/action":[109],"recognition":[110],"benchmarks":[111],"including":[112],"HMDB51,":[113],"UCF101,":[114],"Kinetics.":[116]},"counts_by_year":[{"year":2024,"cited_by_count":2},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
