{"id":"https://openalex.org/W2890162615","doi":"https://doi.org/10.1109/icassp.2018.8462434","title":"Boundary Objectness Network for Object Detection and Localization","display_name":"Boundary Objectness Network for Object Detection and Localization","publication_year":2018,"publication_date":"2018-04-01","ids":{"openalex":"https://openalex.org/W2890162615","doi":"https://doi.org/10.1109/icassp.2018.8462434","mag":"2890162615"},"language":"en","primary_location":{"id":"doi:10.1109/icassp.2018.8462434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/A5100668004","display_name":"Juan Wang","orcid":"https://orcid.org/0000-0002-3848-9433"},"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":"Juan Wang","raw_affiliation_strings":["Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100454105","display_name":"Jie Liu","orcid":"https://orcid.org/0000-0002-4293-4827"},"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":"Xiaoming Tao","raw_affiliation_strings":["Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5079385534","display_name":"Mai Xu","orcid":"https://orcid.org/0000-0002-0277-3301"},"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":"Mai Xu","raw_affiliation_strings":["School of Electronics and Information Engineering, Beihang University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronics and Information Engineering, Beihang University, Beijing, China","institution_ids":["https://openalex.org/I82880672"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053012932","display_name":"Jianhua L\u00fc","orcid":"https://orcid.org/0000-0002-0314-9172"},"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":"Jianhua Lu","raw_affiliation_strings":["Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Tsinghua National Laboratory for Information Science and Technology (TNList), Beijing, China","institution_ids":["https://openalex.org/I99065089"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"2336","last_page":"2340"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","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/T10036","display_name":"Advanced Neural Network Applications","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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9969000220298767,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","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/artificial-intelligence","display_name":"Artificial intelligence","score":0.7608726024627686},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.7567143440246582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7261782288551331},{"id":"https://openalex.org/keywords/minimum-bounding-box","display_name":"Minimum bounding box","score":0.6930304169654846},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.637022852897644},{"id":"https://openalex.org/keywords/boundary","display_name":"Boundary (topology)","score":0.6208802461624146},{"id":"https://openalex.org/keywords/intersection","display_name":"Intersection (aeronautics)","score":0.6130519509315491},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.5876979231834412},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.5762038826942444},{"id":"https://openalex.org/keywords/convolution","display_name":"Convolution (computer science)","score":0.5621318817138672},{"id":"https://openalex.org/keywords/bounding-overwatch","display_name":"Bounding overwatch","score":0.5512637495994568},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5437963008880615},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.49524083733558655},{"id":"https://openalex.org/keywords/margin","display_name":"Margin (machine learning)","score":0.4676377773284912},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.46167847514152527},{"id":"https://openalex.org/keywords/function","display_name":"Function (biology)","score":0.45732179284095764},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.43634289503097534},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.43369007110595703},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.32459282875061035},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.30721795558929443},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.1678503155708313},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.1636420488357544}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7608726024627686},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.7567143440246582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7261782288551331},{"id":"https://openalex.org/C147037132","wikidata":"https://www.wikidata.org/wiki/Q6865426","display_name":"Minimum bounding box","level":3,"score":0.6930304169654846},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.637022852897644},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.6208802461624146},{"id":"https://openalex.org/C64543145","wikidata":"https://www.wikidata.org/wiki/Q162942","display_name":"Intersection (aeronautics)","level":2,"score":0.6130519509315491},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.5876979231834412},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5762038826942444},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.5621318817138672},{"id":"https://openalex.org/C63584917","wikidata":"https://www.wikidata.org/wiki/Q333286","display_name":"Bounding overwatch","level":2,"score":0.5512637495994568},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5437963008880615},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.49524083733558655},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.4676377773284912},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.46167847514152527},{"id":"https://openalex.org/C14036430","wikidata":"https://www.wikidata.org/wiki/Q3736076","display_name":"Function (biology)","level":2,"score":0.45732179284095764},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.43634289503097534},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.43369007110595703},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.32459282875061035},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.30721795558929443},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1678503155708313},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.1636420488357544},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C78458016","wikidata":"https://www.wikidata.org/wiki/Q840400","display_name":"Evolutionary biology","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},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C146978453","wikidata":"https://www.wikidata.org/wiki/Q3798668","display_name":"Aerospace engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icassp.2018.8462434","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icassp.2018.8462434","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","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/W7746136","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1555385401","https://openalex.org/W1686810756","https://openalex.org/W1989684337","https://openalex.org/W2017691720","https://openalex.org/W2066624635","https://openalex.org/W2088049833","https://openalex.org/W2102605133","https://openalex.org/W2163605009","https://openalex.org/W2168356304","https://openalex.org/W2186094539","https://openalex.org/W2519205375","https://openalex.org/W2950094539","https://openalex.org/W2962992847","https://openalex.org/W2963296245","https://openalex.org/W2963446712","https://openalex.org/W3106250896","https://openalex.org/W6600313631","https://openalex.org/W6620707391","https://openalex.org/W6631782140","https://openalex.org/W6633201533","https://openalex.org/W6637373629","https://openalex.org/W6647691147","https://openalex.org/W6654634036","https://openalex.org/W6675026286","https://openalex.org/W6684191040","https://openalex.org/W6685850901","https://openalex.org/W6703839260","https://openalex.org/W6726790931","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W3192357901","https://openalex.org/W3036286480","https://openalex.org/W2387360586","https://openalex.org/W4287027631","https://openalex.org/W4237171675","https://openalex.org/W2952736415","https://openalex.org/W3209723314","https://openalex.org/W3205398323","https://openalex.org/W2883297582","https://openalex.org/W2962677013"],"abstract_inverted_index":{"In":[0,54],"this":[1],"paper,":[2],"we":[3,153],"present":[4],"the":[5,26,29,50,57,66,70,92,98,104,111,114,120,138,143,150,169],"boundary":[6,86,89],"objectness":[7,90],"network":[8,14],"(BON),":[9],"an":[10,95],"effective":[11],"convolutional":[12],"neural":[13],"(CNN)":[15],"for":[16,131,171],"object":[17,96,117],"detection.":[18],"Its":[19],"core":[20],"contribution":[21],"is":[22,59,129],"to":[23,108],"accurately":[24],"localize":[25,110],"objects.":[27],"Generally,":[28],"CNN-based":[30],"localizers":[31],"predict":[32],"four":[33],"bounding":[34],"box":[35],"coordinates":[36],"by":[37],"learning":[38],"a":[39,45,62,76,79,125,159],"regression":[40],"function.":[41],"This":[42],"method":[43],"shows":[44],"low":[46],"Intersection-of-Union":[47],"(IoU)":[48],"with":[49],"ground":[51],"truth":[52],"box.":[53],"our":[55,147],"work,":[56],"localization":[58],"formu-lated":[60],"as":[61],"probabilistic":[63],"problem.":[64],"Specifically,":[65],"deep":[67],"features":[68],"inside":[69],"candidate":[71],"proposal":[72],"are":[73,84],"mapped":[74],"into":[75],"row":[77],"and":[78,100],"column":[80],"feature":[81],"vector,":[82],"which":[83],"called":[85],"object-ness.":[87],"The":[88],"indicates":[91],"existence":[93],"of":[94,103,116,146,161],"in":[97],"horizontal":[99],"vertical":[101],"direction":[102],"proposal,":[105],"enabling":[106],"us":[107],"elaborately":[109],"object.":[112],"Moreover,":[113],"modules":[115],"detection":[118],"share":[119],"common":[121],"convolution-al":[122],"layers.":[123],"Meanwhile,":[124],"multi-task":[126],"loss":[127],"function":[128],"designed":[130],"joint":[132],"training":[133],"strategy.":[134],"Experimental":[135],"results":[136],"on":[137],"PAS-CAL":[139],"VOC":[140],"datasets":[141],"demonstrate":[142],"competitive":[144],"performance":[145],"method.":[148],"For":[149],"VGG16":[151],"model,":[152],"achieve":[154],"77.6":[155],"%":[156],"mAP":[157],"at":[158],"speed":[160],"4":[162],"frame":[163],"per":[164],"second":[165],"(FPS),":[166],"thus":[167],"having":[168],"potential":[170],"real-time":[172],"processing.":[173]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
