{"id":"https://openalex.org/W4385237236","doi":"https://doi.org/10.1109/tgrs.2023.3298661","title":"Transcending Pixels: Boosting Saliency Detection via Scene Understanding From Aerial Imagery","display_name":"Transcending Pixels: Boosting Saliency Detection via Scene Understanding From Aerial Imagery","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4385237236","doi":"https://doi.org/10.1109/tgrs.2023.3298661"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2023.3298661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3298661","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","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/A5036015170","display_name":"Yanfeng Liu","orcid":"https://orcid.org/0000-0003-0122-4463"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Yanfeng Liu","raw_affiliation_strings":["School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5022524675","display_name":"Zhitong Xiong","orcid":"https://orcid.org/0000-0002-3953-585X"},"institutions":[{"id":"https://openalex.org/I62916508","display_name":"Technical University of Munich","ror":"https://ror.org/02kkvpp62","country_code":"DE","type":"education","lineage":["https://openalex.org/I62916508"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Zhitong Xiong","raw_affiliation_strings":["Chair of Data Science in Earth Observation, Technical University of Munich (TUM), Munich, Germany"],"affiliations":[{"raw_affiliation_string":"Chair of Data Science in Earth Observation, Technical University of Munich (TUM), Munich, Germany","institution_ids":["https://openalex.org/I62916508"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100334740","display_name":"Yuan Yuan","orcid":null},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuan Yuan","raw_affiliation_strings":["School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100341321","display_name":"Qi Wang","orcid":"https://orcid.org/0000-0002-7028-4956"},"institutions":[{"id":"https://openalex.org/I17145004","display_name":"Northwestern Polytechnical University","ror":"https://ror.org/01y0j0j86","country_code":"CN","type":"education","lineage":["https://openalex.org/I17145004"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qi Wang","raw_affiliation_strings":["School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and the School of Artificial Intelligence, Optics and Electronics (iOPEN), Northwestern Polytechnical University, Xi’an, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036015170"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":8.0642,"has_fulltext":false,"cited_by_count":67,"citation_normalized_percentile":{"value":0.98353646,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":100},"biblio":{"volume":"61","issue":null,"first_page":"1","last_page":"16"},"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":0.9886000156402588,"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/T11659","display_name":"Advanced Image Fusion Techniques","score":0.9865999817848206,"subfield":{"id":"https://openalex.org/subfields/2214","display_name":"Media Technology"},"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/computer-science","display_name":"Computer science","score":0.8642708659172058},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7063771486282349},{"id":"https://openalex.org/keywords/salient","display_name":"Salient","score":0.6199039220809937},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.6014810800552368},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5470916628837585},{"id":"https://openalex.org/keywords/subnet","display_name":"Subnet","score":0.504625678062439},{"id":"https://openalex.org/keywords/pixel","display_name":"Pixel","score":0.5008456707000732},{"id":"https://openalex.org/keywords/boosting","display_name":"Boosting (machine learning)","score":0.46490490436553955},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.36071377992630005}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8642708659172058},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7063771486282349},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.6199039220809937},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6014810800552368},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5470916628837585},{"id":"https://openalex.org/C21099817","wikidata":"https://www.wikidata.org/wiki/Q7631721","display_name":"Subnet","level":2,"score":0.504625678062439},{"id":"https://openalex.org/C160633673","wikidata":"https://www.wikidata.org/wiki/Q355198","display_name":"Pixel","level":2,"score":0.5008456707000732},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.46490490436553955},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.36071377992630005},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2023.3298661","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2023.3298661","pdf_url":null,"source":{"id":"https://openalex.org/S111326731","display_name":"IEEE Transactions on Geoscience and Remote Sensing","issn_l":"0196-2892","issn":["0196-2892","1558-0644"],"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 Geoscience and Remote Sensing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1964179093","display_name":null,"funder_award_id":"U21B2041","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G2513133394","display_name":null,"funder_award_id":"61825603","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3196644182","display_name":null,"funder_award_id":"U1864204","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":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W1617990436","https://openalex.org/W1965301399","https://openalex.org/W1982075130","https://openalex.org/W2070083314","https://openalex.org/W2100470808","https://openalex.org/W2103504761","https://openalex.org/W2194775991","https://openalex.org/W2295107390","https://openalex.org/W2515866431","https://openalex.org/W2528092473","https://openalex.org/W2560023338","https://openalex.org/W2569272946","https://openalex.org/W2592962403","https://openalex.org/W2620858446","https://openalex.org/W2744613561","https://openalex.org/W2883254424","https://openalex.org/W2884555738","https://openalex.org/W2889835342","https://openalex.org/W2889992972","https://openalex.org/W2890732922","https://openalex.org/W2913087080","https://openalex.org/W2939217524","https://openalex.org/W2948656358","https://openalex.org/W2963529609","https://openalex.org/W2963706010","https://openalex.org/W2963868681","https://openalex.org/W2967085153","https://openalex.org/W2987701848","https://openalex.org/W2998449272","https://openalex.org/W3005521100","https://openalex.org/W3034421924","https://openalex.org/W3034815155","https://openalex.org/W3035026422","https://openalex.org/W3035290198","https://openalex.org/W3035422681","https://openalex.org/W3053564872","https://openalex.org/W3096663231","https://openalex.org/W3096675569","https://openalex.org/W3103611212","https://openalex.org/W3105577662","https://openalex.org/W3107944836","https://openalex.org/W3108948422","https://openalex.org/W3113299742","https://openalex.org/W3131500599","https://openalex.org/W3136512936","https://openalex.org/W3166714471","https://openalex.org/W3169865585","https://openalex.org/W3173370190","https://openalex.org/W3179147540","https://openalex.org/W3188023301","https://openalex.org/W3189874165","https://openalex.org/W3197625928","https://openalex.org/W3200598386","https://openalex.org/W3201616222","https://openalex.org/W3207506706","https://openalex.org/W3208937872","https://openalex.org/W3209073849","https://openalex.org/W3217306379","https://openalex.org/W4205932092","https://openalex.org/W4221014685","https://openalex.org/W4221138999","https://openalex.org/W4224919677","https://openalex.org/W4226291728","https://openalex.org/W4280597585","https://openalex.org/W4290043215","https://openalex.org/W4305005880","https://openalex.org/W4308242054","https://openalex.org/W4310714442","https://openalex.org/W4312373555","https://openalex.org/W4312566218","https://openalex.org/W4312820606","https://openalex.org/W4313525589","https://openalex.org/W4318149001","https://openalex.org/W4365801723","https://openalex.org/W4383220186","https://openalex.org/W4385299230","https://openalex.org/W4387801700","https://openalex.org/W6790114940","https://openalex.org/W6845668075","https://openalex.org/W6846961011","https://openalex.org/W6853090524"],"related_works":["https://openalex.org/W2102539527","https://openalex.org/W2131631951","https://openalex.org/W2356206668","https://openalex.org/W2130707537","https://openalex.org/W3200778902","https://openalex.org/W1977409556","https://openalex.org/W2361602549","https://openalex.org/W4362683600","https://openalex.org/W2963610131","https://openalex.org/W4394867575"],"abstract_inverted_index":{"Existing":[0],"remote":[1,91],"sensing":[2,92],"image":[3],"salient":[4,37,182],"object":[5,163],"detection":[6,46],"(RSI-SOD)":[7],"methods":[8],"widely":[9],"perform":[10,109],"object-level":[11],"semantic":[12],"understanding":[13],"with":[14,36],"pixel-level":[15],"supervision,":[16],"but":[17],"ignore":[18],"the":[19,29,65,81,114,147,152,172,185,206],"image-level":[20,56,82],"scene":[21,30,66,83,93,115,124,148],"information.":[22],"As":[23],"a":[24,32,101,123,130],"fundamental":[25],"attribute":[26],"of":[27,85,97,181],"RSIs,":[28],"has":[31],"complex":[33],"intrinsic":[34],"correlation":[35],"objects,":[38],"which":[39,107],"may":[40],"bring":[41,218],"hints":[42],"to":[43,62,117,155,170,174,214],"improve":[44],"saliency":[45,72,120,140,153,158],"performance.":[47],"However,":[48],"existing":[49],"RSI-SOD":[50,87],"datasets":[51,88],"lack":[52],"both":[53],"pixel-":[54],"and":[55,58,129,150,211],"labels,":[57],"it":[59],"is":[60,168,209],"non-trivial":[61],"effectively":[63],"transfer":[64,126],"domain":[67],"knowledge":[68,111,125],"for":[69,138],"more":[70,176],"accurate":[71,119],"localization.":[73],"To":[74],"address":[75],"these":[76],"challenges,":[77],"we":[78,99,203],"first":[79],"annotate":[80],"labels":[84],"three":[86,200],"inspired":[89],"by":[90],"classification.":[94],"On":[95],"top":[96],"it,":[98],"present":[100],"novel":[102],"scene-guided":[103],"dual-stream":[104],"network":[105],"(SDNet),":[106],"can":[108,217],"cross-task":[110],"distillation":[112],"from":[113,146,184],"classification":[116],"facilitate":[118],"detection.":[121],"Specifically,":[122],"module":[127,134,166],"(SKTM)":[128],"conditional":[131],"dynamic":[132],"guidance":[133],"(CDGM)":[135],"are":[136],"designed":[137],"extracting":[139],"key":[141],"area":[142],"as":[143],"spatial":[144,179],"attention":[145],"subnet":[149,154],"guiding":[151],"generate":[156],"scene-enhanced":[157],"features,":[159],"respectively.":[160],"Finally,":[161],"an":[162],"contour":[164],"awareness":[165],"(OCAM)":[167],"introduced":[169],"enable":[171],"model":[173],"focus":[175],"on":[177,199],"irregular":[178],"details":[180],"objects":[183],"complicated":[186],"background.":[187],"Extensive":[188],"experiments":[189],"reveal":[190],"that":[191,205],"our":[192],"SDNet":[193],"outperforms":[194],"over":[195],"20":[196],"state-of-the-art":[197],"algorithms":[198],"datasets.":[201],"Moreover,":[202],"prove":[204],"proposed":[207],"framework":[208],"model-agnostic,":[210],"its":[212],"extension":[213],"six":[215],"baselines":[216],"significant":[219],"performance":[220],"benefits.":[221],"Code":[222],"will":[223],"be":[224],"available":[225],"at":[226],"https://github.com/lyf0801/SDNet.":[227]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":34},{"year":2024,"cited_by_count":30},{"year":2023,"cited_by_count":1}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}