{"id":"https://openalex.org/W3195624337","doi":"https://doi.org/10.1109/icip42928.2021.9506630","title":"Deep Active Learning For Human Pose Estimation Via Consistency Weighted Core-Set Approach","display_name":"Deep Active Learning For Human Pose Estimation Via Consistency Weighted Core-Set Approach","publication_year":2021,"publication_date":"2021-08-23","ids":{"openalex":"https://openalex.org/W3195624337","doi":"https://doi.org/10.1109/icip42928.2021.9506630","mag":"3195624337"},"language":"en","primary_location":{"id":"doi:10.1109/icip42928.2021.9506630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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/A5055409222","display_name":"Wuqiang Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Wuqiang Zhang","raw_affiliation_strings":["Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077111461","display_name":"Zijie Guo","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zijie Guo","raw_affiliation_strings":["Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062933258","display_name":"Rong Zhi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rong Zhi","raw_affiliation_strings":["Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037408275","display_name":"Wang Baofeng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Baofeng Wang","raw_affiliation_strings":["Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China"],"affiliations":[{"raw_affiliation_string":"Daimler Greater China,Mercedes-Benz Research &#x0026; Development Center,Beijing,China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5055409222"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.3843,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.60666667,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"909","last_page":"913"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9988999962806702,"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":0.9988999962806702,"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":0.9983000159263611,"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/T12072","display_name":"Machine Learning and Algorithms","score":0.9950000047683716,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.743054211139679},{"id":"https://openalex.org/keywords/consistency","display_name":"Consistency (knowledge bases)","score":0.701189398765564},{"id":"https://openalex.org/keywords/representativeness-heuristic","display_name":"Representativeness heuristic","score":0.6922396421432495},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.592754065990448},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.5595979690551758},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5562449097633362},{"id":"https://openalex.org/keywords/core","display_name":"Core (optical fiber)","score":0.5390962362289429},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4811016917228699},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.47414132952690125},{"id":"https://openalex.org/keywords/selection","display_name":"Selection (genetic algorithm)","score":0.4695870280265808},{"id":"https://openalex.org/keywords/domain-adaptation","display_name":"Domain adaptation","score":0.4606897830963135},{"id":"https://openalex.org/keywords/annotation","display_name":"Annotation","score":0.44375649094581604},{"id":"https://openalex.org/keywords/active-learning","display_name":"Active learning (machine learning)","score":0.4329306483268738},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4175630211830139},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3645400404930115},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.13105759024620056}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.743054211139679},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.701189398765564},{"id":"https://openalex.org/C37381756","wikidata":"https://www.wikidata.org/wiki/Q20203288","display_name":"Representativeness heuristic","level":2,"score":0.6922396421432495},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.592754065990448},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.5595979690551758},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5562449097633362},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.5390962362289429},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4811016917228699},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.47414132952690125},{"id":"https://openalex.org/C81917197","wikidata":"https://www.wikidata.org/wiki/Q628760","display_name":"Selection (genetic algorithm)","level":2,"score":0.4695870280265808},{"id":"https://openalex.org/C2776434776","wikidata":"https://www.wikidata.org/wiki/Q19246213","display_name":"Domain adaptation","level":3,"score":0.4606897830963135},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.44375649094581604},{"id":"https://openalex.org/C77967617","wikidata":"https://www.wikidata.org/wiki/Q4677561","display_name":"Active learning (machine learning)","level":2,"score":0.4329306483268738},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4175630211830139},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3645400404930115},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.13105759024620056},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.0},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.0},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip42928.2021.9506630","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip42928.2021.9506630","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 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":27,"referenced_works":["https://openalex.org/W1975672287","https://openalex.org/W1978633512","https://openalex.org/W2080873731","https://openalex.org/W2115305054","https://openalex.org/W2625559849","https://openalex.org/W2774918944","https://openalex.org/W2777262900","https://openalex.org/W2798820905","https://openalex.org/W2891932097","https://openalex.org/W2910982074","https://openalex.org/W2916798096","https://openalex.org/W2956371155","https://openalex.org/W2984303785","https://openalex.org/W2986514296","https://openalex.org/W3010360081","https://openalex.org/W3035166710","https://openalex.org/W3035499919","https://openalex.org/W3047531357","https://openalex.org/W3091287244","https://openalex.org/W3107725941","https://openalex.org/W3110608319","https://openalex.org/W3208337321","https://openalex.org/W4287692693","https://openalex.org/W6739899774","https://openalex.org/W6747231328","https://openalex.org/W6758233323","https://openalex.org/W6761126960"],"related_works":["https://openalex.org/W3159631231","https://openalex.org/W4306248409","https://openalex.org/W4211213551","https://openalex.org/W2332151799","https://openalex.org/W2062728131","https://openalex.org/W1824075546","https://openalex.org/W2103926897","https://openalex.org/W2101250918","https://openalex.org/W4376143407","https://openalex.org/W2894406327"],"abstract_inverted_index":{"Aiming":[0],"to":[1,12],"develop":[2],"an":[3,59],"annotation-efficient":[4],"algorithm":[5],"by":[6,32],"selecting":[7],"the":[8,28,35,78],"most":[9],"informative":[10],"samples":[11],"be":[13],"labeled":[14],"for":[15],"human":[16],"pose":[17],"estimation,":[18],"we":[19],"propose":[20],"a":[21],"novel":[22],"active":[23],"learning":[24],"approach":[25,31,85],"that":[26,46],"generalized":[27],"standard":[29],"core-set":[30],"dynamically":[33],"incorporating":[34],"uncertainty":[36],"and":[37,52,74,80],"representativeness":[38],"cues.":[39],"Based":[40],"on":[41,70],"our":[42,56,83],"designed":[43],"assignment":[44],"cost":[45],"consists":[47],"of":[48,82],"fast":[49],"spatial":[50],"consistency":[51],"domain-shift":[53],"scaled":[54],"distance,":[55],"method":[57],"proposed":[58,84],"adaptive":[60],"information":[61],"measurement":[62],"as":[63],"data":[64],"selection":[65],"criterion.":[66],"Extensive":[67],"experiments":[68],"conducted":[69],"two":[71],"network":[72],"architectures":[73],"various":[75],"datasets":[76],"demonstrate":[77],"effectiveness":[79],"superiority":[81],"in":[86],"comparison":[87],"with":[88],"other":[89],"state-of-the-art":[90],"methods.":[91]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
