{"id":"https://openalex.org/W3134912427","doi":"https://doi.org/10.1109/tip.2021.3060167","title":"CDNet: Complementary Depth Network for RGB-D Salient Object Detection","display_name":"CDNet: Complementary Depth Network for RGB-D Salient Object Detection","publication_year":2021,"publication_date":"2021-01-01","ids":{"openalex":"https://openalex.org/W3134912427","doi":"https://doi.org/10.1109/tip.2021.3060167","mag":"3134912427","pmid":"https://pubmed.ncbi.nlm.nih.gov/33646949"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2021.3060167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3060167","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Image Processing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","pubmed"],"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/A5031324242","display_name":"Wenda Jin","orcid":"https://orcid.org/0000-0001-5964-4781"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Wen-Da Jin","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5042967567","display_name":"Jun Xu","orcid":"https://orcid.org/0000-0002-1602-538X"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Xu","raw_affiliation_strings":["School of Statistics and Data Science, Nankai University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"School of Statistics and Data Science, Nankai University, Tianjin, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100717223","display_name":"Qi Han","orcid":"https://orcid.org/0000-0002-0597-5419"},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Han","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, TKLNDST, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, TKLNDST, China","institution_ids":["https://openalex.org/I205237279"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100653792","display_name":"Yi Zhang","orcid":"https://orcid.org/0000-0003-2297-2954"},"institutions":[{"id":"https://openalex.org/I162868743","display_name":"Tianjin University","ror":"https://ror.org/012tb2g32","country_code":"CN","type":"education","lineage":["https://openalex.org/I162868743"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yi Zhang","raw_affiliation_strings":["College of Intelligence and Computing, Tianjin University, Tianjin, China"],"affiliations":[{"raw_affiliation_string":"College of Intelligence and Computing, Tianjin University, Tianjin, China","institution_ids":["https://openalex.org/I162868743"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5037131575","display_name":"Ming\u2010Ming Cheng","orcid":null},"institutions":[{"id":"https://openalex.org/I205237279","display_name":"Nankai University","ror":"https://ror.org/01y1kjr75","country_code":"CN","type":"education","lineage":["https://openalex.org/I205237279"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ming-Ming Cheng","raw_affiliation_strings":["College of Computer Science, Nankai University, Tianjin, TKLNDST, China"],"affiliations":[{"raw_affiliation_string":"College of Computer Science, Nankai University, Tianjin, TKLNDST, China","institution_ids":["https://openalex.org/I205237279"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5031324242"],"corresponding_institution_ids":["https://openalex.org/I162868743"],"apc_list":null,"apc_paid":null,"fwci":13.3711,"has_fulltext":false,"cited_by_count":163,"citation_normalized_percentile":{"value":0.99244782,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"30","issue":null,"first_page":"3376","last_page":"3390"},"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9921000003814697,"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":0.9829999804496765,"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/rgb-color-model","display_name":"RGB color model","score":0.882672905921936},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.746736466884613},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.682483434677124},{"id":"https://openalex.org/keywords/leverage","display_name":"Leverage (statistics)","score":0.5572390556335449},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5144343972206116},{"id":"https://openalex.org/keywords/depth-map","display_name":"Depth map","score":0.5016202926635742},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.47745683789253235},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.44537854194641113},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.42263007164001465},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.41689029335975647},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.1496986746788025},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.07474786043167114}],"concepts":[{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.882672905921936},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.746736466884613},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.682483434677124},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.5572390556335449},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5144343972206116},{"id":"https://openalex.org/C141268832","wikidata":"https://www.wikidata.org/wiki/Q2940499","display_name":"Depth map","level":3,"score":0.5016202926635742},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47745683789253235},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.44537854194641113},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.42263007164001465},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.41689029335975647},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.1496986746788025},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.07474786043167114},{"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/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2021.3060167","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2021.3060167","pdf_url":null,"source":{"id":"https://openalex.org/S4210173141","display_name":"IEEE Transactions on Image Processing","issn_l":"1057-7149","issn":["1057-7149","1941-0042"],"is_oa":false,"is_in_doaj":false,"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 Transactions on Image Processing","raw_type":"journal-article"},{"id":"pmid:33646949","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/33646949","pdf_url":null,"source":{"id":"https://openalex.org/S4306525036","display_name":"PubMed","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I1299303238","host_organization_name":"National Institutes of Health","host_organization_lineage":["https://openalex.org/I1299303238"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE transactions on image processing : a publication of the IEEE Signal Processing Society","raw_type":null}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1586258774","display_name":null,"funder_award_id":"62002176","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6420215544","display_name":null,"funder_award_id":"61702359","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"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":85,"referenced_works":["https://openalex.org/W20683899","https://openalex.org/W1665214252","https://openalex.org/W1772076007","https://openalex.org/W1901129140","https://openalex.org/W1938386764","https://openalex.org/W1966025376","https://openalex.org/W1976409045","https://openalex.org/W1976754232","https://openalex.org/W1993713494","https://openalex.org/W2019584258","https://openalex.org/W2031489346","https://openalex.org/W2033959528","https://openalex.org/W2037954058","https://openalex.org/W2039298799","https://openalex.org/W2058359403","https://openalex.org/W2069241582","https://openalex.org/W2090518410","https://openalex.org/W2100470808","https://openalex.org/W2108598243","https://openalex.org/W2154063764","https://openalex.org/W2198724430","https://openalex.org/W2253986341","https://openalex.org/W2337762808","https://openalex.org/W2461758788","https://openalex.org/W2514453564","https://openalex.org/W2520640394","https://openalex.org/W2523246573","https://openalex.org/W2561238782","https://openalex.org/W2600144439","https://openalex.org/W2620958690","https://openalex.org/W2765838470","https://openalex.org/W2766315367","https://openalex.org/W2798857366","https://openalex.org/W2887522866","https://openalex.org/W2901017177","https://openalex.org/W2909381593","https://openalex.org/W2939217524","https://openalex.org/W2948300571","https://openalex.org/W2948510860","https://openalex.org/W2957414648","https://openalex.org/W2962159375","https://openalex.org/W2962680827","https://openalex.org/W2962741298","https://openalex.org/W2962946266","https://openalex.org/W2963112696","https://openalex.org/W2963529609","https://openalex.org/W2963591054","https://openalex.org/W2963868681","https://openalex.org/W2964105864","https://openalex.org/W2967622921","https://openalex.org/W2971137300","https://openalex.org/W2986825110","https://openalex.org/W2989161706","https://openalex.org/W3002301267","https://openalex.org/W3003376220","https://openalex.org/W3010616503","https://openalex.org/W3022015146","https://openalex.org/W3034320133","https://openalex.org/W3034429256","https://openalex.org/W3035284915","https://openalex.org/W3035357085","https://openalex.org/W3035633116","https://openalex.org/W3035687312","https://openalex.org/W3049194477","https://openalex.org/W3099871687","https://openalex.org/W3101633331","https://openalex.org/W3102457447","https://openalex.org/W3104979525","https://openalex.org/W3106587394","https://openalex.org/W3108421143","https://openalex.org/W3108822985","https://openalex.org/W3115654959","https://openalex.org/W3120113457","https://openalex.org/W3125703990","https://openalex.org/W4239147634","https://openalex.org/W4293390340","https://openalex.org/W6637242042","https://openalex.org/W6639824700","https://openalex.org/W6648922525","https://openalex.org/W6682370321","https://openalex.org/W6727249380","https://openalex.org/W6730179637","https://openalex.org/W6779749348","https://openalex.org/W6780629296","https://openalex.org/W6785161788"],"related_works":["https://openalex.org/W2378211422","https://openalex.org/W4321353415","https://openalex.org/W2745001401","https://openalex.org/W2130974462","https://openalex.org/W2028665553","https://openalex.org/W2086519370","https://openalex.org/W4246352526","https://openalex.org/W2121910908","https://openalex.org/W915438175","https://openalex.org/W2003805688"],"abstract_inverted_index":{"Current":[0],"RGB-D":[1,28,32,61,72,153,166],"salient":[2],"object":[3],"detection":[4],"(SOD)":[5],"methods":[6],"utilize":[7],"the":[8,15,19,65,82,111,116,138,142,147],"depth":[9,20,58,69,79,92,98,112,120,139],"stream":[10],"as":[11,81],"complementary":[12],"information":[13],"to":[14,54,71,76,89,95,109,135],"RGB":[16,87,143],"stream.":[17],"However,":[18],"maps":[21,70,80,121],"are":[22],"usually":[23],"of":[24,67,149],"low-quality":[25,68],"in":[26],"existing":[27],"SOD":[29,33,167],"datasets.":[30],"Most":[31],"networks":[34],"trained":[35],"with":[36,122,141],"these":[37],"datasets":[38,159],"would":[39],"produce":[40],"error-prone":[41],"results.":[42],"In":[43],"this":[44],"paper,":[45],"we":[46,74,103,127],"propose":[47,75,104],"a":[48,105,129],"novel":[49],"Complementary":[50],"Depth":[51],"Network":[52],"(CDNet)":[53],"well":[55,136],"exploit":[56],"saliency-informative":[57,78],"features":[59,88,99,113,140],"for":[60,100],"SOD.":[62,154],"To":[63],"alleviate":[64],"influence":[66],"SOD,":[73],"select":[77],"training":[83],"targets":[84],"and":[85,118],"leverage":[86],"estimate":[90],"meaningful":[91],"maps.":[93],"Besides,":[94],"learn":[96],"robust":[97],"accurate":[101],"prediction,":[102],"new":[106],"dynamic":[107],"scheme":[108,134],"fuse":[110],"extracted":[114],"from":[115],"original":[117],"estimated":[119],"adaptive":[123],"weights.":[124],"What's":[125],"more,":[126],"design":[128],"two-stage":[130],"cross-modal":[131],"feature":[132],"fusion":[133],"integrate":[137],"ones,":[144],"further":[145],"improving":[146],"performance":[148],"our":[150,162],"CDNet":[151,163],"on":[152,156],"Experiments":[155],"seven":[157],"benchmark":[158],"demonstrate":[160],"that":[161],"outperforms":[164],"state-of-the-art":[165],"methods.":[168],"The":[169],"code":[170],"is":[171],"publicly":[172],"available":[173],"at":[174],"https://github.com/blanclist/CDNet.":[175]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":22},{"year":2024,"cited_by_count":42},{"year":2023,"cited_by_count":50},{"year":2022,"cited_by_count":37},{"year":2021,"cited_by_count":9}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}
