{"id":"https://openalex.org/W2976674591","doi":"https://doi.org/10.1109/tmm.2019.2943740","title":"Multi-View Saliency Guided Deep Neural Network for 3-D Object Retrieval and Classification","display_name":"Multi-View Saliency Guided Deep Neural Network for 3-D Object Retrieval and Classification","publication_year":2019,"publication_date":"2019-09-28","ids":{"openalex":"https://openalex.org/W2976674591","doi":"https://doi.org/10.1109/tmm.2019.2943740","mag":"2976674591"},"language":"en","primary_location":{"id":"doi:10.1109/tmm.2019.2943740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2019.2943740","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-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/A5042213182","display_name":"Heyu Zhou","orcid":null},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"He-Yu Zhou","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-9451-5600","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5081485810","display_name":"An-An Liu","orcid":"https://orcid.org/0000-0001-5755-9145"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"An-An Liu","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0001-5755-9145","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5001185571","display_name":"Weizhi Nie","orcid":"https://orcid.org/0000-0002-0578-8138"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wei-Zhi Nie","raw_affiliation_strings":["School of Electrical and Information Engineering, Tianjin University, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-0578-8138","affiliations":[{"raw_affiliation_string":"School of Electrical and Information Engineering, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058652390","display_name":"Jie Nie","orcid":"https://orcid.org/0000-0003-4952-7666"},"institutions":[{"id":"https://openalex.org/I59028903","display_name":"Ocean University of China","ror":"https://ror.org/04rdtx186","country_code":"CN","type":"education","lineage":["https://openalex.org/I59028903"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jie Nie","raw_affiliation_strings":["College of Information Science and Engineering, Ocean University of China, Qingdao, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"College of Information Science and Engineering, Ocean University of China, Qingdao, China","institution_ids":["https://openalex.org/I59028903"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.1004,"has_fulltext":false,"cited_by_count":78,"citation_normalized_percentile":{"value":0.98499935,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"22","issue":"6","first_page":"1496","last_page":"1506"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9997000098228455,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10812","display_name":"Human Pose and Action Recognition","score":0.9980000257492065,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9975000023841858,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/computer-science","display_name":"Computer science","score":0.8862642049789429},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7781842947006226},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6568661332130432},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.6445909142494202},{"id":"https://openalex.org/keywords/rendering","display_name":"Rendering (computer graphics)","score":0.5816985368728638},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5166147351264954},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5137356519699097},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49983930587768555},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.4693388044834137},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.45792990922927856},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.4317081868648529},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.41943663358688354},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.4122235178947449},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.36646485328674316}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8862642049789429},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7781842947006226},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6568661332130432},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.6445909142494202},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.5816985368728638},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5166147351264954},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5137356519699097},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49983930587768555},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.4693388044834137},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.45792990922927856},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.4317081868648529},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.41943663358688354},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.4122235178947449},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.36646485328674316},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tmm.2019.2943740","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tmm.2019.2943740","pdf_url":null,"source":{"id":"https://openalex.org/S137030581","display_name":"IEEE Transactions on Multimedia","issn_l":"1520-9210","issn":["1520-9210","1941-0077"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Multimedia","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7099999785423279}],"awards":[{"id":"https://openalex.org/G1149763565","display_name":"\u57fa\u4e8e\u6df1\u5ea6\u5b66\u4e60\u7684\u4e09\u7ef4\u6a21\u578b\u68c0\u7d22\u7b97\u6cd5\u7814\u7a76","funder_award_id":"61872267","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2050428177","display_name":"\u591a\u6a21\u8026\u5408\u7684\u5f00\u653e\u96c6\u89c6\u9891\u81ea\u52a8\u89e3\u6790\u65b9\u6cd5\u7814\u7a76","funder_award_id":"61772359","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6928944096","display_name":null,"funder_award_id":"61702471","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":58,"referenced_works":["https://openalex.org/W577846486","https://openalex.org/W1482825550","https://openalex.org/W1484544914","https://openalex.org/W1540630416","https://openalex.org/W1644641054","https://openalex.org/W1920022804","https://openalex.org/W1976664910","https://openalex.org/W2002552945","https://openalex.org/W2003402419","https://openalex.org/W2012673871","https://openalex.org/W2019894188","https://openalex.org/W2021122545","https://openalex.org/W2028248716","https://openalex.org/W2059917035","https://openalex.org/W2068078373","https://openalex.org/W2069870183","https://openalex.org/W2106629076","https://openalex.org/W2123977795","https://openalex.org/W2137914836","https://openalex.org/W2151103935","https://openalex.org/W2163605009","https://openalex.org/W2165939338","https://openalex.org/W2190691619","https://openalex.org/W2211722331","https://openalex.org/W2318793210","https://openalex.org/W2342223463","https://openalex.org/W2412404627","https://openalex.org/W2518780089","https://openalex.org/W2526428212","https://openalex.org/W2546066744","https://openalex.org/W2555254696","https://openalex.org/W2580018057","https://openalex.org/W2608645542","https://openalex.org/W2618530766","https://openalex.org/W2768213582","https://openalex.org/W2779039928","https://openalex.org/W2794206172","https://openalex.org/W2801933800","https://openalex.org/W2885093977","https://openalex.org/W2887582123","https://openalex.org/W2893150766","https://openalex.org/W2911195052","https://openalex.org/W2962724911","https://openalex.org/W2962731536","https://openalex.org/W2962876561","https://openalex.org/W2962928871","https://openalex.org/W2963121255","https://openalex.org/W2964342398","https://openalex.org/W4394671432","https://openalex.org/W6640300118","https://openalex.org/W6676085277","https://openalex.org/W6687484953","https://openalex.org/W6729001083","https://openalex.org/W6732640084","https://openalex.org/W6736612982","https://openalex.org/W6739778489","https://openalex.org/W6746340398","https://openalex.org/W6754044394"],"related_works":["https://openalex.org/W2965546495","https://openalex.org/W4389116644","https://openalex.org/W2153315159","https://openalex.org/W3103844505","https://openalex.org/W259157601","https://openalex.org/W4205463238","https://openalex.org/W2761785940","https://openalex.org/W2110523656","https://openalex.org/W1482209366","https://openalex.org/W2521627374"],"abstract_inverted_index":{"In":[0],"this":[1],"paper,":[2],"we":[3],"propose":[4],"the":[5,28,38,46,53,68,74,85,93,99,121,127,139,166,179,184],"multi-view":[6,79,88,133,143],"saliency":[7,69],"guided":[8],"deep":[9],"neural":[10],"network":[11],"(MVSG-DNN)":[12],"for":[13,58,103,161],"3D":[14,43,95,104,156],"object":[15,96,105,157],"retrieval":[16,106,158],"and":[17,65,107,126,159,176],"classification.":[18,108],"This":[19],"method":[20],"mainly":[21],"consists":[22],"of":[23,30,41,48,62,87,123,142,147,181],"three":[24],"key":[25],"modules.":[26],"First,":[27],"module":[29,47,86],"model":[31],"projection":[32],"rendering":[33],"is":[34],"employed":[35],"to":[36,71],"capture":[37],"multiple":[39],"views":[40,64,76,125],"one":[42],"object.":[44],"Second,":[45],"visual":[49,59],"context":[50],"learning":[51,90],"applies":[52],"basic":[54],"Convolutional":[55],"Neural":[56],"Networks":[57],"feature":[60],"extraction":[61],"individual":[63],"then":[66],"employs":[67],"LSTM":[70,102],"adaptively":[72],"select":[73],"representative":[75,124],"based":[77],"on":[78,173],"context.":[80],"Finally,":[81],"with":[82,98],"these":[83],"information,":[84],"representation":[89],"can":[91,118,137,153],"generate":[92],"compile":[94],"descriptors":[97],"designed":[100],"classification":[101,160],"The":[109],"proposed":[110],"MVSG-DNN":[111,182],"has":[112],"two":[113],"main":[114],"contributions:":[115],"1)":[116],"It":[117,136],"jointly":[119],"realize":[120],"selection":[122],"similarity":[128],"measure":[129],"by":[130,164],"fully":[131],"exploiting":[132],"context;":[134],"2)":[135],"discover":[138],"discriminative":[140],"structure":[141],"sequence":[144],"without":[145],"constraints":[146],"specific":[148],"camera":[149,168],"settings.":[150,169],"Consequently,":[151],"it":[152],"support":[154],"flexible":[155],"real":[162],"applications":[163],"avoiding":[165],"required":[167],"Extensive":[170],"comparison":[171],"experiments":[172],"ModelNet10,":[174],"ModelNet40,":[175],"ShapeNetCore55":[177],"demonstrate":[178],"superiority":[180],"against":[183],"state-of-art":[185],"methods.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":13},{"year":2023,"cited_by_count":17},{"year":2022,"cited_by_count":16},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":8}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}