{"id":"https://openalex.org/W2970662571","doi":"https://doi.org/10.1109/icip.2019.8803088","title":"Atrous Temporal Convolutional Network for Video Action Segmentation","display_name":"Atrous Temporal Convolutional Network for Video Action Segmentation","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970662571","doi":"https://doi.org/10.1109/icip.2019.8803088","mag":"2970662571"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE International Conference on Image Processing (ICIP)","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/A5108891681","display_name":"Jiahao Wang","orcid":"https://orcid.org/0009-0000-5496-9720"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Jiahao Wang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023256496","display_name":"Zhengyin Du","orcid":"https://orcid.org/0000-0003-0338-4225"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhengyin Du","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5012121355","display_name":"Annan Li","orcid":"https://orcid.org/0000-0003-3497-5052"},"institutions":[{"id":"https://openalex.org/I4210165198","display_name":"Beijing Advanced Sciences and Innovation Center","ror":"https://ror.org/05qm21180","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210165198"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Annan Li","raw_affiliation_strings":["Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beijing Advanced Innovation Center for Big Data and Brain Computing, Beijing, China","institution_ids":["https://openalex.org/I4210165198"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100398953","display_name":"Yunhong Wang","orcid":"https://orcid.org/0000-0001-8001-2703"},"institutions":[{"id":"https://openalex.org/I82880672","display_name":"Beihang University","ror":"https://ror.org/00wk2mp56","country_code":"CN","type":"education","lineage":["https://openalex.org/I82880672"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yunhong Wang","raw_affiliation_strings":["Beihang University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5108891681"],"corresponding_institution_ids":["https://openalex.org/I82880672"],"apc_list":null,"apc_paid":null,"fwci":0.92,"has_fulltext":false,"cited_by_count":13,"citation_normalized_percentile":{"value":0.79425815,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1585","last_page":"1589"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9998999834060669,"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":0.9998999834060669,"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/T10331","display_name":"Video Surveillance and Tracking Methods","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/T10036","display_name":"Advanced Neural Network Applications","score":0.996999979019165,"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":0.7726147770881653},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.767884373664856},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7212777137756348},{"id":"https://openalex.org/keywords/pooling","display_name":"Pooling","score":0.6798694133758545},{"id":"https://openalex.org/keywords/pyramid","display_name":"Pyramid (geometry)","score":0.6577915549278259},{"id":"https://openalex.org/keywords/encoder","display_name":"Encoder","score":0.5571286678314209},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.504430890083313},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4589274227619171},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.45604777336120605},{"id":"https://openalex.org/keywords/convolutional-code","display_name":"Convolutional code","score":0.44214504957199097},{"id":"https://openalex.org/keywords/action","display_name":"Action (physics)","score":0.4147673547267914},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.32912003993988037},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.09927687048912048},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.07885146141052246}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7726147770881653},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.767884373664856},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7212777137756348},{"id":"https://openalex.org/C70437156","wikidata":"https://www.wikidata.org/wiki/Q7228652","display_name":"Pooling","level":2,"score":0.6798694133758545},{"id":"https://openalex.org/C142575187","wikidata":"https://www.wikidata.org/wiki/Q3358290","display_name":"Pyramid (geometry)","level":2,"score":0.6577915549278259},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.5571286678314209},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.504430890083313},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4589274227619171},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.45604777336120605},{"id":"https://openalex.org/C157899210","wikidata":"https://www.wikidata.org/wiki/Q1395022","display_name":"Convolutional code","level":3,"score":0.44214504957199097},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.4147673547267914},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.32912003993988037},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.09927687048912048},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.07885146141052246},{"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},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803088","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803088","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 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":30,"referenced_works":["https://openalex.org/W1522301498","https://openalex.org/W1610060839","https://openalex.org/W1815076433","https://openalex.org/W1936750108","https://openalex.org/W1949049686","https://openalex.org/W2031688197","https://openalex.org/W2109698606","https://openalex.org/W2194775991","https://openalex.org/W2402144811","https://openalex.org/W2412782625","https://openalex.org/W2413983136","https://openalex.org/W2461621749","https://openalex.org/W2491875666","https://openalex.org/W2519091744","https://openalex.org/W2550143307","https://openalex.org/W2792764867","https://openalex.org/W2799262584","https://openalex.org/W2949382160","https://openalex.org/W2953384591","https://openalex.org/W2960672642","https://openalex.org/W2963840672","https://openalex.org/W2964121744","https://openalex.org/W2964309882","https://openalex.org/W4251033893","https://openalex.org/W6631190155","https://openalex.org/W6638545294","https://openalex.org/W6696085341","https://openalex.org/W6713134421","https://openalex.org/W6748481559","https://openalex.org/W6749825310"],"related_works":["https://openalex.org/W2022849497","https://openalex.org/W2407190427","https://openalex.org/W3081299480","https://openalex.org/W2132373020","https://openalex.org/W2919210741","https://openalex.org/W2907584218","https://openalex.org/W3002446410","https://openalex.org/W2096049278","https://openalex.org/W2221419418","https://openalex.org/W4390224712"],"abstract_inverted_index":{"Fine-grained":[0],"temporal":[1,35,68,82],"human":[2],"action":[3,27,48,111],"segmentation":[4,28,112],"in":[5,17,41],"untrimmed":[6],"videos":[7],"is":[8,23],"receiving":[9],"increasing":[10],"attention":[11],"due":[12],"to":[13,30,33,56,108],"its":[14],"extensive":[15],"applications":[16,43],"surveillance,":[18],"robotics,":[19],"and":[20,86,120],"beyond.":[21],"It":[22],"crucial":[24],"for":[25],"an":[26,47,88],"system":[29],"be":[31],"robust":[32],"the":[34,44,96,116,129,132],"scale":[36],"of":[37,46,58,90,131],"different":[38],"actions":[39],"since":[40],"practical":[42],"duration":[45],"can":[49],"vary":[50],"from":[51],"less":[52],"than":[53],"a":[54,65],"second":[55],"tens":[57],"minutes.":[59],"In":[60,95],"this":[61],"paper,":[62],"we":[63],"introduce":[64],"novel":[66],"atrous":[67,81],"convolutional":[69,93],"network":[70],"(AT-Net),":[71],"which":[72],"explicitly":[73],"generates":[74],"multiscale":[75,101],"video":[76],"contextual":[77,102],"representations":[78],"by":[79],"utilizing":[80],"pyramid":[83],"pooling":[84],"(ATPP)":[85],"has":[87],"architecture":[89],"encoder-decoder":[91],"fully":[92],"network.":[94],"decoding":[97],"stage,":[98],"AT-Net":[99,125],"combines":[100],"features":[103,107],"with":[104],"low-level":[105],"local":[106],"generate":[109],"high-quality":[110],"results.":[113],"Experiments":[114],"on":[115],"50":[117],"Salads,":[118],"GTEA":[119],"JIGSAWS":[121],"benchmarks":[122],"demonstrate":[123],"that":[124],"achieves":[126],"improvement":[127],"over":[128],"state":[130],"art.":[133]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":2},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":2}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}
