{"id":"https://openalex.org/W4385341347","doi":"https://doi.org/10.1142/s0218001423500234","title":"Depth-Constrained Network for Multi-Scale Object Detection","display_name":"Depth-Constrained Network for Multi-Scale Object Detection","publication_year":2023,"publication_date":"2023-07-28","ids":{"openalex":"https://openalex.org/W4385341347","doi":"https://doi.org/10.1142/s0218001423500234"},"language":"en","primary_location":{"id":"doi:10.1142/s0218001423500234","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001423500234","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","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/A5100380157","display_name":"Guohua Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tianjin Polytechnic University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Guohua Liu","raw_affiliation_strings":["School of Mechanical Engineering, Tiangong University, No. 399 Binshui West Road, Xiqing District, Tianjin 300387, P. R. China"],"affiliations":[{"raw_affiliation_string":"School of Mechanical Engineering, Tiangong University, No. 399 Binshui West Road, Xiqing District, Tianjin 300387, P. R. China","institution_ids":["https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100447651","display_name":"Yijun Li","orcid":"https://orcid.org/0009-0008-9170-3786"},"institutions":[{"id":"https://openalex.org/I198091727","display_name":"Tianjin Polytechnic University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yijun Li","raw_affiliation_strings":["Tianjin Key Laboratory of Advanced Mechatronics Equipment Technology, Tiangong University, No. 399 Binshui West Road, Xiqing District, Tianjin 300387, P. R. China"],"affiliations":[{"raw_affiliation_string":"Tianjin Key Laboratory of Advanced Mechatronics Equipment Technology, Tiangong University, No. 399 Binshui West Road, Xiqing District, Tianjin 300387, P. R. China","institution_ids":["https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5100380157"],"corresponding_institution_ids":["https://openalex.org/I198091727"],"apc_list":null,"apc_paid":null,"fwci":0.123,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.39636547,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":"37","issue":"10","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9986000061035156,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.996999979019165,"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":0.8067742586135864},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7512233257293701},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.5671878457069397},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5623698830604553},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.5456321239471436},{"id":"https://openalex.org/keywords/modal","display_name":"Modal","score":0.5142895579338074},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5139105319976807},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5063210725784302},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4998776912689209},{"id":"https://openalex.org/keywords/enhanced-data-rates-for-gsm-evolution","display_name":"Enhanced Data Rates for GSM Evolution","score":0.44957882165908813},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3975982666015625},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.34187063574790955}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8067742586135864},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7512233257293701},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.5671878457069397},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5623698830604553},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.5456321239471436},{"id":"https://openalex.org/C71139939","wikidata":"https://www.wikidata.org/wiki/Q910194","display_name":"Modal","level":2,"score":0.5142895579338074},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5139105319976807},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5063210725784302},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4998776912689209},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.44957882165908813},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3975982666015625},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.34187063574790955},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C188027245","wikidata":"https://www.wikidata.org/wiki/Q750446","display_name":"Polymer chemistry","level":1,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1142/s0218001423500234","is_oa":false,"landing_page_url":"https://doi.org/10.1142/s0218001423500234","pdf_url":null,"source":{"id":"https://openalex.org/S41486457","display_name":"International Journal of Pattern Recognition and Artificial Intelligence","issn_l":"0218-0014","issn":["0218-0014","1793-6381"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319815","host_organization_name":"World Scientific","host_organization_lineage":["https://openalex.org/P4310319815"],"host_organization_lineage_names":["World Scientific"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"International Journal of Pattern Recognition and Artificial Intelligence","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.550000011920929,"display_name":"Reduced inequalities"},{"id":"https://metadata.un.org/sdg/16","score":0.4099999964237213,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W2115579991","https://openalex.org/W2957414648","https://openalex.org/W2965779981","https://openalex.org/W3197599997","https://openalex.org/W3201085820","https://openalex.org/W3212386989","https://openalex.org/W4206222731","https://openalex.org/W4214930627","https://openalex.org/W4229005449","https://openalex.org/W4231777370","https://openalex.org/W4290043875","https://openalex.org/W4291653252","https://openalex.org/W4309010643","https://openalex.org/W4320033720","https://openalex.org/W4321438890"],"related_works":["https://openalex.org/W2168109476","https://openalex.org/W2486460843","https://openalex.org/W1968121071","https://openalex.org/W2379392295","https://openalex.org/W3160965418","https://openalex.org/W2020254986","https://openalex.org/W613940353","https://openalex.org/W2061647633","https://openalex.org/W2038374617","https://openalex.org/W1992540108"],"abstract_inverted_index":{"Challenges":[0],"such":[1],"as":[2,89],"complex":[3],"backgrounds,":[4],"drastic":[5],"variations":[6],"in":[7,14,167],"target":[8],"scales,":[9],"and":[10,27,44,49,71,92,94,120,128,139],"dense":[11],"distributions":[12],"exist":[13],"natural":[15],"scenes.":[16],"Some":[17],"algorithms":[18],"optimize":[19],"multi-scale":[20,55,62,105],"object":[21,63,69],"detection":[22,56,64,70,87],"performance":[23],"by":[24],"combining":[25],"low-level":[26,121],"high-level":[28],"information":[29,91,127,136,147],"through":[30,74],"feature":[31],"fusion":[32,113],"strategies.":[33],"However,":[34],"these":[35],"methods":[36,157],"overlook":[37],"the":[38,45,54,86,159,171,177,184],"inherent":[39],"spatial":[40,99],"properties":[41],"of":[42,165,179],"objects":[43],"relationships":[46],"between":[47,104],"foreground":[48],"background.":[50],"To":[51],"fundamentally":[52],"enhance":[53],"capability,":[57],"we":[58,175],"propose":[59],"a":[60,75,110],"depth-constrained":[61],"network":[65],"that":[66,116,152],"simultaneously":[67],"learns":[68],"depth":[72,81,118,141],"estimation":[73],"unified":[76],"framework.":[77],"In":[78],"this":[79],"network,":[80],"features":[82,142],"are":[83],"merged":[84],"into":[85],"branch":[88],"auxiliary":[90],"constrained":[93],"guided":[95],"to":[96,124,143],"obtain":[97],"better":[98,145],"representations,":[100],"which":[101],"enhances":[102],"discrimination":[103],"objects.":[106],"We":[107,133],"also":[108],"introduce":[109],"novel":[111],"cross-modal":[112],"(CmF)":[114],"strategy":[115],"utilizes":[117],"awareness":[119],"detail":[122],"clues":[123],"supplement":[125],"edge":[126],"adjust":[129],"attention":[130],"weight":[131],"preferences.":[132],"find":[134],"complementary":[135],"from":[137],"RGB":[138],"high-quality":[140],"achieve":[144],"multi-modal":[146],"fusion.":[148],"Experimental":[149],"results":[150],"demonstrate":[151],"our":[153,180],"method":[154,182],"outperforms":[155],"state-of-the-art":[156],"on":[158,183],"KINS":[160],"dataset,":[161],"with":[162],"an":[163],"improvement":[164],"3.0%":[166],"AP":[168],"score":[169],"over":[170],"baseline":[172],"network.":[173],"Furthermore,":[174],"validate":[176],"effectiveness":[178],"proposed":[181],"KITTI":[185],"dataset.":[186]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
