{"id":"https://openalex.org/W2970287256","doi":"https://doi.org/10.1109/icip.2019.8803783","title":"Temporal Feature Enhancing Network for Human Pose Estimation in Videos","display_name":"Temporal Feature Enhancing Network for Human Pose Estimation in Videos","publication_year":2019,"publication_date":"2019-08-26","ids":{"openalex":"https://openalex.org/W2970287256","doi":"https://doi.org/10.1109/icip.2019.8803783","mag":"2970287256"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2019.8803783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803783","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/A5043036615","display_name":"Haihan Li","orcid":"https://orcid.org/0000-0002-5399-5094"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Haihan Li","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026184280","display_name":"Wenming Yang","orcid":"https://orcid.org/0000-0002-2506-1286"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenming Yang","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5009239895","display_name":"Qingmin Liao","orcid":"https://orcid.org/0000-0002-7509-3964"},"institutions":[{"id":"https://openalex.org/I99065089","display_name":"Tsinghua University","ror":"https://ror.org/03cve4549","country_code":"CN","type":"education","lineage":["https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingmin Liao","raw_affiliation_strings":["Tsinghua University, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Tsinghua University, Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5043036615"],"corresponding_institution_ids":["https://openalex.org/I99065089"],"apc_list":null,"apc_paid":null,"fwci":0.3037,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.60376334,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"579","last_page":"583"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9995999932289124,"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":0.9995999932289124,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.9977999925613403,"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":0.9972000122070312,"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":0.8259953856468201},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.8071839809417725},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.7025836706161499},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6846778392791748},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.6533246040344238},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6498915553092957},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6128686666488647},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5665279626846313},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5654018521308899},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.5306970477104187},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5207238793373108},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.46400418877601624},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.41735079884529114},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3951660990715027},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38434267044067383},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.3065958023071289},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.12082749605178833}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8259953856468201},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.8071839809417725},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7025836706161499},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6846778392791748},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.6533246040344238},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6498915553092957},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6128686666488647},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5665279626846313},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5654018521308899},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.5306970477104187},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5207238793373108},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.46400418877601624},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.41735079884529114},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3951660990715027},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38434267044067383},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.3065958023071289},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.12082749605178833},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2019.8803783","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2019.8803783","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":26,"referenced_works":["https://openalex.org/W764651262","https://openalex.org/W1936750108","https://openalex.org/W2031489346","https://openalex.org/W2034014085","https://openalex.org/W2552900565","https://openalex.org/W2554082199","https://openalex.org/W2604346130","https://openalex.org/W2620105270","https://openalex.org/W2625614184","https://openalex.org/W2887240357","https://openalex.org/W2959975024","https://openalex.org/W2962849564","https://openalex.org/W2963150697","https://openalex.org/W2963708869","https://openalex.org/W2963759896","https://openalex.org/W2963866658","https://openalex.org/W2964084369","https://openalex.org/W2964185410","https://openalex.org/W2964286567","https://openalex.org/W2964304707","https://openalex.org/W6729953642","https://openalex.org/W6735463952","https://openalex.org/W6739112683","https://openalex.org/W6746925369","https://openalex.org/W6748370023","https://openalex.org/W6757221710"],"related_works":["https://openalex.org/W2946083937","https://openalex.org/W2798721181","https://openalex.org/W2951583186","https://openalex.org/W4299867837","https://openalex.org/W2088028039","https://openalex.org/W4382141741","https://openalex.org/W4386075737","https://openalex.org/W1968783203","https://openalex.org/W4206633503","https://openalex.org/W2574567538"],"abstract_inverted_index":{"Although":[0],"state-of-the-art":[1],"methods":[2],"for":[3,60],"human":[4,62],"pose":[5,63,106,122],"estimation":[6,123],"have":[7],"achieved":[8],"superior":[9],"results":[10,110],"on":[11,17,118],"the":[12,38,47,67,85,112,115],"single":[13],"image,":[14],"their":[15],"performance":[16],"videos":[18],"usually":[19],"deteriorates":[20],"dramatically":[21],"due":[22],"to":[23,45,104],"motion":[24,72],"blur":[25],"and":[26,79,97],"occlusion.":[27],"Since":[28],"there":[29],"is":[30,92],"close":[31],"temporal":[32,81],"correlation":[33],"among":[34],"video":[35,61,105,121],"frames,":[36],"exploiting":[37],"contextual":[39],"information":[40,73],"properly":[41],"can":[42,98],"be":[43],"helpful":[44],"tackle":[46],"problem.":[48],"In":[49],"this":[50],"paper,":[51],"we":[52],"present":[53],"a":[54],"Temporal":[55],"Feature":[56],"Enhancing":[57],"Network":[58],"(TFEN)":[59],"estimation.":[64,107],"It":[65,91],"boosts":[66],"per-frame":[68],"features":[69],"by":[70,84],"utilizing":[71],"in":[74],"terms":[75],"of":[76,114],"optical":[77],"flow":[78],"conducting":[80],"feature":[82],"encoding":[83],"convolution":[86],"gated":[87],"recurrent":[88],"units":[89],"(convGRU).":[90],"an":[93],"end-to-end":[94],"learning":[95],"framework":[96],"extend":[99],"any":[100],"image":[101],"based":[102],"algorithm":[103],"The":[108],"experimental":[109],"validate":[111],"effectiveness":[113],"proposed":[116],"approach":[117],"two":[119],"large-scale":[120],"benchmarks.":[124]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}