{"id":"https://openalex.org/W3031338878","doi":"https://doi.org/10.1109/access.2020.2997982","title":"Multi-Level Context Aggregation Network With Channel-Wise Attention for Salient Object Detection","display_name":"Multi-Level Context Aggregation Network With Channel-Wise Attention for Salient Object Detection","publication_year":2020,"publication_date":"2020-01-01","ids":{"openalex":"https://openalex.org/W3031338878","doi":"https://doi.org/10.1109/access.2020.2997982","mag":"3031338878"},"language":"en","primary_location":{"id":"doi:10.1109/access.2020.2997982","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2997982","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09102278.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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/ielx7/6287639/8948470/09102278.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5103235153","display_name":"Zihui Jia","orcid":"https://orcid.org/0000-0002-3625-0218"},"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":"Zihui Jia","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0002-3625-0218","affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5067922510","display_name":"Zhenyu Weng","orcid":"https://orcid.org/0000-0001-7857-8687"},"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":"Zhenyu Weng","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0001-7857-8687","affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103035430","display_name":"Fang Wan","orcid":"https://orcid.org/0000-0003-0140-2952"},"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":"Fang Wan","raw_affiliation_strings":["School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-0140-2952","affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China","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":["School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2524-6800","affiliations":[{"raw_affiliation_string":"School of Electronic and Computer Engineering, Peking University Shenzhen Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"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":0.0979,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.38242595,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":"8","issue":null,"first_page":"102303","last_page":"102312"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","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/T11605","display_name":"Visual Attention and Saliency Detection","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/T10036","display_name":"Advanced Neural Network Applications","score":0.9853000044822693,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9818999767303467,"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":0.8690879344940186},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.7845631837844849},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6542918682098389},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6141047477722168},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.5801032781600952},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.5619250535964966},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5267291069030762},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5085068941116333},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4854882061481476},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4807845950126648},{"id":"https://openalex.org/keywords/backbone-network","display_name":"Backbone network","score":0.4536456763744354},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4491996169090271},{"id":"https://openalex.org/keywords/channel","display_name":"Channel (broadcasting)","score":0.4398467540740967},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.4358314275741577},{"id":"https://openalex.org/keywords/top-down-and-bottom-up-design","display_name":"Top-down and bottom-up design","score":0.41870737075805664}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8690879344940186},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.7845631837844849},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6542918682098389},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6141047477722168},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.5801032781600952},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.5619250535964966},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5267291069030762},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5085068941116333},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4854882061481476},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4807845950126648},{"id":"https://openalex.org/C88796919","wikidata":"https://www.wikidata.org/wiki/Q1142907","display_name":"Backbone network","level":2,"score":0.4536456763744354},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4491996169090271},{"id":"https://openalex.org/C127162648","wikidata":"https://www.wikidata.org/wiki/Q16858953","display_name":"Channel (broadcasting)","level":2,"score":0.4398467540740967},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.4358314275741577},{"id":"https://openalex.org/C135798126","wikidata":"https://www.wikidata.org/wiki/Q2167279","display_name":"Top-down and bottom-up design","level":2,"score":0.41870737075805664},{"id":"https://openalex.org/C159985019","wikidata":"https://www.wikidata.org/wiki/Q181790","display_name":"Composite material","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},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","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},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C115903868","wikidata":"https://www.wikidata.org/wiki/Q80993","display_name":"Software engineering","level":1,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","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/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C192562407","wikidata":"https://www.wikidata.org/wiki/Q228736","display_name":"Materials science","level":0,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2020.2997982","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2997982","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09102278.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:6baa98e2179647e2acc6ef889a5c49cc","is_oa":true,"landing_page_url":"https://doaj.org/article/6baa98e2179647e2acc6ef889a5c49cc","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 8, Pp 102303-102312 (2020)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2020.2997982","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2020.2997982","pdf_url":"https://ieeexplore.ieee.org/ielx7/6287639/8948470/09102278.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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G2433373925","display_name":null,"funder_award_id":"U1613215","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"},{"id":"https://openalex.org/F4320327511","display_name":"Development and Reform Commission of Shenzhen Municipality","ror":"https://ror.org/03jmg4515"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3031338878.pdf","grobid_xml":"https://content.openalex.org/works/W3031338878.grobid-xml"},"referenced_works_count":49,"referenced_works":["https://openalex.org/W845365781","https://openalex.org/W1522301498","https://openalex.org/W1686810756","https://openalex.org/W1836465849","https://openalex.org/W1854404533","https://openalex.org/W1894057436","https://openalex.org/W1903029394","https://openalex.org/W2002781701","https://openalex.org/W2037954058","https://openalex.org/W2039313011","https://openalex.org/W2060095179","https://openalex.org/W2086791339","https://openalex.org/W2108598243","https://openalex.org/W2162681317","https://openalex.org/W2293332611","https://openalex.org/W2338972621","https://openalex.org/W2415535521","https://openalex.org/W2519528544","https://openalex.org/W2740667773","https://openalex.org/W2744613561","https://openalex.org/W2752782242","https://openalex.org/W2798791651","https://openalex.org/W2799074129","https://openalex.org/W2807746031","https://openalex.org/W2939217524","https://openalex.org/W2944209449","https://openalex.org/W2948500402","https://openalex.org/W2948510860","https://openalex.org/W2949117887","https://openalex.org/W2961348656","https://openalex.org/W2962680827","https://openalex.org/W2963032190","https://openalex.org/W2963299740","https://openalex.org/W2963420686","https://openalex.org/W2963685207","https://openalex.org/W2963868681","https://openalex.org/W2964101377","https://openalex.org/W2982331121","https://openalex.org/W2986825110","https://openalex.org/W2987701848","https://openalex.org/W2990984982","https://openalex.org/W2996884277","https://openalex.org/W4239147634","https://openalex.org/W6631190155","https://openalex.org/W6637373629","https://openalex.org/W6638667902","https://openalex.org/W6638992375","https://openalex.org/W6639359414","https://openalex.org/W6769982728"],"related_works":["https://openalex.org/W2468279273","https://openalex.org/W2354198838","https://openalex.org/W1989130879","https://openalex.org/W2103419012","https://openalex.org/W2329500892","https://openalex.org/W1974414866","https://openalex.org/W28991112","https://openalex.org/W2064871819","https://openalex.org/W2054945203","https://openalex.org/W2149051193"],"abstract_inverted_index":{"Fully":[0],"convolutional":[1],"neural":[2],"networks":[3],"(FCNs)":[4],"have":[5],"shown":[6],"their":[7,162],"advantages":[8],"in":[9,23,77,87,108,190],"the":[10,16,42,52,74,110,121,127,135,212],"salient":[11],"object":[12,31],"detection":[13],"task.":[14],"However,":[15],"prediction":[17],"results":[18],"do":[19],"not":[20,141],"perform":[21,209],"well":[22],"most":[24],"existing":[25],"FCN-based":[26],"methods,":[27],"such":[28],"as":[29],"coarse":[30],"boundaries":[32],"or":[33,50],"even":[34],"getting":[35],"wrong":[36],"predictions,":[37],"which":[38,78,176],"resulted":[39],"from":[40,117,126,137],"ignoring":[41],"difference":[43],"between":[44],"multi-level":[45,67,146,157],"features":[46,98,102,116,136,158,172],"during":[47],"feature":[48,147],"aggregation":[49,69,148],"underutilizing":[51],"spatial":[53,182],"details":[54,97,183],"suitable":[55],"for":[56],"locating":[57],"boundaries.":[58],"In":[59],"this":[60],"paper,":[61],"we":[62],"propose":[63],"a":[64,88,145],"novel":[65],"end-to-end":[66],"context":[68],"network":[70],"(MLCANet)":[71],"to":[72,120,155,168,186],"solve":[73],"problem":[75],"mentioned-above,":[76],"both":[79],"bottom-up":[80,91],"and":[81,107,164,181,208,218],"top-down":[82,111],"message":[83,174],"passing":[84,175],"can":[85,199],"cooperate":[86],"joint":[89],"manner.The":[90],"process":[92,112],"that":[93,113,134,196],"aggregates":[94],"low-level":[95],"fine":[96],"into":[99],"high-level":[100,105,129],"semantically-richer":[101],"would":[103],"enhance":[104],"features,":[106],"turn":[109],"passes":[114],"refined":[115],"deeper":[118],"layers":[119,139],"shallower":[122],"ones":[123],"could":[124],"benefit":[125],"enhanced":[128],"features.":[130],"Also":[131],"by":[132,159],"considering":[133],"different":[138],"may":[140],"be":[142],"equally":[143],"important,":[144],"mechanism":[149],"with":[150,205],"channel-wise":[151],"attention":[152],"is":[153],"proposed":[154],"aggregate":[156],"flexibly":[160],"adjusting":[161],"contributions":[163],"absorbing":[165],"useful":[166],"information":[167,180],"refine":[169],"themselves.":[170],"The":[171],"after":[173],"simultaneously":[177],"encode":[178],"semantic":[179],"are":[184],"used":[185],"predict":[187],"saliency":[188,203],"maps":[189,204],"our":[191,197],"network.":[192],"Extensive":[193],"experiments":[194],"demonstrate":[195],"method":[198],"obtain":[200],"high":[201],"quality":[202],"clear":[206],"boundaries,":[207],"favorably":[210],"against":[211],"state-of-the-art":[213],"methods":[214],"without":[215],"any":[216],"pre-processing":[217],"post-processing.":[219]},"counts_by_year":[{"year":2020,"cited_by_count":1}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
