{"id":"https://openalex.org/W2790967904","doi":"https://doi.org/10.1109/icip.2017.8297070","title":"Pedestrian detection with dynamic iterative bootstrapping","display_name":"Pedestrian detection with dynamic iterative bootstrapping","publication_year":2017,"publication_date":"2017-09-01","ids":{"openalex":"https://openalex.org/W2790967904","doi":"https://doi.org/10.1109/icip.2017.8297070","mag":"2790967904"},"language":"en","primary_location":{"id":"doi:10.1109/icip.2017.8297070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8297070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","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/A5022113605","display_name":"Chao Pei","orcid":"https://orcid.org/0009-0009-6278-350X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chao Pei","raw_affiliation_strings":["Communication and Information Security Lab, Shenzhen Graduate School, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication and Information Security Lab, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100605728","display_name":"Lei Hao","orcid":"https://orcid.org/0000-0002-4535-7375"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lei Hao","raw_affiliation_strings":["Communication and Information Security Lab, Shenzhen Graduate School, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication and Information Security Lab, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5056706680","display_name":"Yuesheng Zhu","orcid":"https://orcid.org/0000-0003-2524-6800"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuesheng Zhu","raw_affiliation_strings":["Communication and Information Security Lab, Shenzhen Graduate School, Peking University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Communication and Information Security Lab, Shenzhen Graduate School, Peking University","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"4182","last_page":"4186"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9997000098228455,"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":0.9995999932289124,"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/T11512","display_name":"Anomaly Detection Techniques and Applications","score":0.9957000017166138,"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":0.8407453298568726},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6741206645965576},{"id":"https://openalex.org/keywords/bootstrapping","display_name":"Bootstrapping (finance)","score":0.6570451855659485},{"id":"https://openalex.org/keywords/pedestrian-detection","display_name":"Pedestrian detection","score":0.6423910856246948},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.5704593658447266},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5679637789726257},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5206105709075928},{"id":"https://openalex.org/keywords/convergence","display_name":"Convergence (economics)","score":0.4832907021045685},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.46533671021461487},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4642561078071594},{"id":"https://openalex.org/keywords/iterative-method","display_name":"Iterative method","score":0.43225085735321045},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4312344789505005},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.42276644706726074},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.24559053778648376}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8407453298568726},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6741206645965576},{"id":"https://openalex.org/C207609745","wikidata":"https://www.wikidata.org/wiki/Q4944086","display_name":"Bootstrapping (finance)","level":2,"score":0.6570451855659485},{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.6423910856246948},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5704593658447266},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5679637789726257},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5206105709075928},{"id":"https://openalex.org/C2777303404","wikidata":"https://www.wikidata.org/wiki/Q759757","display_name":"Convergence (economics)","level":2,"score":0.4832907021045685},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.46533671021461487},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4642561078071594},{"id":"https://openalex.org/C159694833","wikidata":"https://www.wikidata.org/wiki/Q2321565","display_name":"Iterative method","level":2,"score":0.43225085735321045},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4312344789505005},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.42276644706726074},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.24559053778648376},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","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/C22212356","wikidata":"https://www.wikidata.org/wiki/Q775325","display_name":"Transport engineering","level":1,"score":0.0},{"id":"https://openalex.org/C50522688","wikidata":"https://www.wikidata.org/wiki/Q189833","display_name":"Economic growth","level":1,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C106159729","wikidata":"https://www.wikidata.org/wiki/Q2294553","display_name":"Financial economics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icip.2017.8297070","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icip.2017.8297070","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE International Conference on Image Processing (ICIP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320327511","display_name":"Development and Reform Commission of Shenzhen Municipality","ror":"https://ror.org/03jmg4515"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W219040644","https://openalex.org/W345900524","https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1554705102","https://openalex.org/W1650122911","https://openalex.org/W1686810756","https://openalex.org/W1903127635","https://openalex.org/W2031454541","https://openalex.org/W2041497292","https://openalex.org/W2074777933","https://openalex.org/W2077513643","https://openalex.org/W2088049833","https://openalex.org/W2097117768","https://openalex.org/W2116022929","https://openalex.org/W2140090057","https://openalex.org/W2151103935","https://openalex.org/W2161969291","https://openalex.org/W2162741153","https://openalex.org/W2168356304","https://openalex.org/W2170101770","https://openalex.org/W2174940656","https://openalex.org/W2200528286","https://openalex.org/W2613718673","https://openalex.org/W2963516811","https://openalex.org/W4294583774","https://openalex.org/W6611649897","https://openalex.org/W6620707391","https://openalex.org/W6636787326","https://openalex.org/W6660695881","https://openalex.org/W6684811926"],"related_works":["https://openalex.org/W1534274833","https://openalex.org/W3117246195","https://openalex.org/W156620619","https://openalex.org/W2098233217","https://openalex.org/W2914363205","https://openalex.org/W2616249226","https://openalex.org/W2997844990","https://openalex.org/W1598221548","https://openalex.org/W2972620127","https://openalex.org/W2981141433"],"abstract_inverted_index":{"Recent":[0],"years":[1],"have":[2],"seen":[3],"the":[4,53,58,69,77,80,89,100,123],"increasing":[5],"importance":[6],"of":[7,79],"pedestrian":[8,25],"detection,":[9],"which":[10,106],"is":[11,96],"a":[12,23,63],"key":[13],"problem":[14],"in":[15,57,103,129],"computer":[16],"vision.":[17],"In":[18,32],"this":[19],"paper,":[20],"we":[21,61],"propose":[22,62],"novel":[24],"detection":[26],"approach":[27,125],"based":[28],"on":[29,115],"Faster":[30],"R-CNN.":[31],"order":[33],"to":[34,87,98],"obtain":[35],"high-quality":[36],"candidate":[37],"regions,":[38],"relevant":[39],"adjustments":[40],"with":[41,131],"more":[42,91],"precise":[43],"anchors":[44],"are":[45,73,82],"made":[46],"for":[47],"region":[48],"proposal":[49],"network.":[50],"To":[51],"resolve":[52],"data":[54],"imbalance":[55],"issue":[56],"classifier":[59],"training,":[60],"dynamic":[64],"iterative":[65],"bootstrapping":[66],"method":[67,95],"where":[68],"hard":[70],"negative":[71],"examples":[72],"automatically":[74],"selected":[75],"and":[76,110],"weights":[78],"network":[81],"updated":[83],"iteratively":[84],"by":[85],"them":[86],"make":[88],"training":[90],"effective.":[92],"The":[93],"square":[94],"used":[97,118],"optimize":[99],"multi-task":[101],"loss":[102],"our":[104],"approach,":[105],"can":[107],"accelerate":[108],"convergence":[109],"reduce":[111],"sensitivity.":[112],"Experimental":[113],"results":[114],"different":[116],"widely":[117],"benchmark":[119],"datasets":[120],"show":[121],"that":[122],"proposed":[124],"achieves":[126],"better":[127],"performance":[128],"comparison":[130],"other":[132],"common":[133],"methods.":[134]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}