{"id":"https://openalex.org/W2913803398","doi":"https://doi.org/10.1109/access.2019.2896201","title":"Deep Feature Fusion by Competitive Attention for Pedestrian Detection","display_name":"Deep Feature Fusion by Competitive Attention for Pedestrian Detection","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2913803398","doi":"https://doi.org/10.1109/access.2019.2896201","mag":"2913803398"},"language":"en","primary_location":{"id":"doi:10.1109/access.2019.2896201","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2896201","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08629899.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08629899.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5061268953","display_name":"Zhichang Chen","orcid":"https://orcid.org/0000-0001-8225-3527"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhichang Chen","raw_affiliation_strings":["Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100425661","display_name":"Li Zhang","orcid":"https://orcid.org/0000-0002-9115-6718"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Li Zhang","raw_affiliation_strings":["Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-9115-6718","affiliations":[{"raw_affiliation_string":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000178744","display_name":"Abdul Mateen Khattak","orcid":"https://orcid.org/0000-0003-4417-489X"},"institutions":[{"id":"https://openalex.org/I246743127","display_name":"The University of Agriculture, Peshawar","ror":"https://ror.org/02sp3q482","country_code":"PK","type":"education","lineage":["https://openalex.org/I246743127"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Abdul Mateen Khattak","raw_affiliation_strings":["Department of Horticulture, The University of Agriculture, Peshawar, Pakistan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Horticulture, The University of Agriculture, Peshawar, Pakistan","institution_ids":["https://openalex.org/I246743127"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5013019306","display_name":"Wanlin Gao","orcid":"https://orcid.org/0000-0002-4845-4541"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanlin Gao","raw_affiliation_strings":["Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4845-4541","affiliations":[{"raw_affiliation_string":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China","institution_ids":["https://openalex.org/I4210151987"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013774822","display_name":"Minjuan Wang","orcid":"https://orcid.org/0000-0002-7520-1726"},"institutions":[{"id":"https://openalex.org/I4210151987","display_name":"Ministry of Agriculture and Rural Affairs","ror":"https://ror.org/05ckt8b96","country_code":"CN","type":"government","lineage":["https://openalex.org/I4210127390","https://openalex.org/I4210151987"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minjuan Wang","raw_affiliation_strings":["Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-7520-1726","affiliations":[{"raw_affiliation_string":"Key Laboratory of Agricultural Informatization Standardization, Ministry of Agriculture and Rural Affairs, Beijing, China","institution_ids":["https://openalex.org/I4210151987"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":0.5955,"has_fulltext":true,"cited_by_count":7,"citation_normalized_percentile":{"value":0.70764379,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"7","issue":null,"first_page":"21981","last_page":"21989"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9994999766349792,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.9983000159263611,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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/pedestrian-detection","display_name":"Pedestrian detection","score":0.8655999898910522},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8173085451126099},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.7965214252471924},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.7333735227584839},{"id":"https://openalex.org/keywords/pedestrian","display_name":"Pedestrian","score":0.6928184032440186},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6851186752319336},{"id":"https://openalex.org/keywords/architecture","display_name":"Architecture","score":0.6646021604537964},{"id":"https://openalex.org/keywords/block","display_name":"Block (permutation group theory)","score":0.6056277751922607},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5223087668418884},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.4982178211212158},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.49026039242744446},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.47928160429000854},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.46823185682296753},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3625651001930237},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.36064672470092773},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.09679403901100159},{"id":"https://openalex.org/keywords/computer-security","display_name":"Computer security","score":0.061157435178756714}],"concepts":[{"id":"https://openalex.org/C2780156472","wikidata":"https://www.wikidata.org/wiki/Q2355550","display_name":"Pedestrian detection","level":3,"score":0.8655999898910522},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8173085451126099},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7965214252471924},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.7333735227584839},{"id":"https://openalex.org/C2777113093","wikidata":"https://www.wikidata.org/wiki/Q221488","display_name":"Pedestrian","level":2,"score":0.6928184032440186},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6851186752319336},{"id":"https://openalex.org/C123657996","wikidata":"https://www.wikidata.org/wiki/Q12271","display_name":"Architecture","level":2,"score":0.6646021604537964},{"id":"https://openalex.org/C2777210771","wikidata":"https://www.wikidata.org/wiki/Q4927124","display_name":"Block (permutation group theory)","level":2,"score":0.6056277751922607},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5223087668418884},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.4982178211212158},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.49026039242744446},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.47928160429000854},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.46823185682296753},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3625651001930237},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.36064672470092773},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.09679403901100159},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.061157435178756714},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C142362112","wikidata":"https://www.wikidata.org/wiki/Q735","display_name":"Art","level":0,"score":0.0},{"id":"https://openalex.org/C153349607","wikidata":"https://www.wikidata.org/wiki/Q36649","display_name":"Visual arts","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2019.2896201","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2896201","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08629899.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:5a3e49b95de54b2987de074726792a23","is_oa":true,"landing_page_url":"https://doaj.org/article/5a3e49b95de54b2987de074726792a23","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 7, Pp 21981-21989 (2019)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2019.2896201","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2019.2896201","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8600701/08629899.pdf","source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"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 Access","raw_type":"journal-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6933372382","display_name":null,"funder_award_id":"2017PT19","funder_id":"https://openalex.org/F4320321106","funder_display_name":"Ministry of Education of the People's Republic of China"},{"id":"https://openalex.org/G8025746936","display_name":null,"funder_award_id":"2018M630222","funder_id":"https://openalex.org/F4320321543","funder_display_name":"China Postdoctoral Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320321106","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934"},{"id":"https://openalex.org/F4320321543","display_name":"China Postdoctoral Science Foundation","ror":"https://ror.org/0426zh255"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2913803398.pdf","grobid_xml":"https://content.openalex.org/works/W2913803398.grobid-xml"},"referenced_works_count":53,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W1536680647","https://openalex.org/W1650122911","https://openalex.org/W1861492603","https://openalex.org/W2034779469","https://openalex.org/W2036989445","https://openalex.org/W2074777933","https://openalex.org/W2081021369","https://openalex.org/W2098064689","https://openalex.org/W2102605133","https://openalex.org/W2107775979","https://openalex.org/W2117687030","https://openalex.org/W2120419212","https://openalex.org/W2123099218","https://openalex.org/W2136724559","https://openalex.org/W2150066425","https://openalex.org/W2161969291","https://openalex.org/W2166623283","https://openalex.org/W2170101770","https://openalex.org/W2194775991","https://openalex.org/W2200528286","https://openalex.org/W2265127172","https://openalex.org/W2490270993","https://openalex.org/W2497039038","https://openalex.org/W2531915888","https://openalex.org/W2548197316","https://openalex.org/W2565639579","https://openalex.org/W2608295741","https://openalex.org/W2613599172","https://openalex.org/W2743905801","https://openalex.org/W2752782242","https://openalex.org/W2785700004","https://openalex.org/W2883795007","https://openalex.org/W2884188791","https://openalex.org/W2888728082","https://openalex.org/W2963037989","https://openalex.org/W2963315052","https://openalex.org/W2963815618","https://openalex.org/W2963998989","https://openalex.org/W2964052344","https://openalex.org/W3106250896","https://openalex.org/W6636787326","https://openalex.org/W6639102338","https://openalex.org/W6674977583","https://openalex.org/W6683411478","https://openalex.org/W6684811926","https://openalex.org/W6693705612","https://openalex.org/W6722946945","https://openalex.org/W6723816956","https://openalex.org/W6749996660","https://openalex.org/W6750371988","https://openalex.org/W6753997096","https://openalex.org/W6785652829"],"related_works":["https://openalex.org/W2972620127","https://openalex.org/W2981141433","https://openalex.org/W2802018156","https://openalex.org/W2101531944","https://openalex.org/W4313315626","https://openalex.org/W4312696271","https://openalex.org/W4223892596","https://openalex.org/W2933098581","https://openalex.org/W2556125083","https://openalex.org/W3204901196"],"abstract_inverted_index":{"Pedestrian":[0],"detection":[1,31],"is":[2,22],"a":[3,51,102,143],"key":[4],"problem":[5],"for":[6,46,118],"automatic":[7],"driving,":[8],"and":[9,69,90,115],"the":[10,27,63,74,97,109,124],"results":[11,135],"have":[12],"been":[13],"improved":[14],"significantly":[15],"via":[16],"deep":[17],"convolutional":[18],"networks.":[19],"However,":[20],"there":[21],"still":[23],"room":[24],"to":[25,54,111],"improve":[26],"performance":[28],"of":[29,42,83],"pedestrian":[30,47,119],"by":[32],"carefully":[33],"dealing":[34],"with":[35,94,101,123,139],"some":[36],"critical":[37],"issues.":[38],"To":[39],"take":[40],"advantages":[41],"more":[43,113],"discriminative":[44],"information":[45,61,72],"detection,":[48],"we":[49],"propose":[50],"novel":[52],"architecture":[53,81,107,129,141],"auto-choose":[55],"semantic":[56],"as":[57,59],"well":[58],"specific":[60],"among":[62,73],"feature":[64,75,84,91],"maps":[65,76,85,92],"at":[66],"different":[67,88],"levels":[68,89],"integrate":[70],"valuable":[71],"in":[77,87],"multi-scales.":[78,95],"Particularly,":[79],"our":[80,128],"consists":[82],"concatenating":[86],"integrating":[93],"Both":[96],"operations":[98],"are":[99],"equipped":[100],"competitive":[103],"attention":[104],"block.":[105],"The":[106,133],"has":[108],"ability":[110],"obtain":[112],"efficient":[114],"discriminating":[116],"features":[117],"detection.":[120],"In":[121],"comparison":[122],"other":[125],"prevailing":[126],"models,":[127],"provides":[130],"superior":[131],"performance.":[132],"promising":[134],"achieved":[136],"through":[137],"experimentation":[138],"this":[140],"achieve":[142],"new":[144],"state-of-the-art":[145],"on":[146],"Caltech":[147],"dataset.":[148]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
