{"id":"https://openalex.org/W4318149001","doi":"https://doi.org/10.1109/tip.2023.3238648","title":"RSSFormer: Foreground Saliency Enhancement for Remote Sensing Land-Cover Segmentation","display_name":"RSSFormer: Foreground Saliency Enhancement for Remote Sensing Land-Cover Segmentation","publication_year":2023,"publication_date":"2023-01-01","ids":{"openalex":"https://openalex.org/W4318149001","doi":"https://doi.org/10.1109/tip.2023.3238648","pmid":"https://pubmed.ncbi.nlm.nih.gov/37022079"},"language":"en","primary_location":{"id":"doi:10.1109/tip.2023.3238648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3238648","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/A5038918940","display_name":"Rongtao Xu","orcid":"https://orcid.org/0000-0003-4619-9679"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rongtao Xu","raw_affiliation_strings":["National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4619-9679","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020628396","display_name":"Changwei Wang","orcid":"https://orcid.org/0000-0001-8259-7717"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Changwei Wang","raw_affiliation_strings":["National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-8259-7717","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101620304","display_name":"Jiguang Zhang","orcid":"https://orcid.org/0000-0002-8212-1361"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiguang Zhang","raw_affiliation_strings":["National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011919230","display_name":"Shibiao Xu","orcid":"https://orcid.org/0000-0003-4037-9900"},"institutions":[{"id":"https://openalex.org/I139759216","display_name":"Beijing University of Posts and Telecommunications","ror":"https://ror.org/04w9fbh59","country_code":"CN","type":"education","lineage":["https://openalex.org/I139759216"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shibiao Xu","raw_affiliation_strings":["School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4037-9900","affiliations":[{"raw_affiliation_string":"School of Artificial Intelligence, Beijing University of Posts and Telecommunications, Beijing, China","institution_ids":["https://openalex.org/I139759216"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5112127114","display_name":"Weiliang Meng","orcid":"https://orcid.org/0000-0002-3221-4981"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiliang Meng","raw_affiliation_strings":["National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-3221-4981","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100667567","display_name":"Xiaopeng Zhang","orcid":"https://orcid.org/0000-0002-0092-6474"},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210112150","display_name":"Institute of Automation","ror":"https://ror.org/022c3hy66","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210112150"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xiaopeng Zhang","raw_affiliation_strings":["National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0092-6474","affiliations":[{"raw_affiliation_string":"National Laboratory of Pattern Recognition, School of Artificial Intelligence, Institute of Automation, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210112150","https://openalex.org/I19820366"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":6,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":19.3118,"has_fulltext":false,"cited_by_count":172,"citation_normalized_percentile":{"value":0.99624751,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"32","issue":null,"first_page":"1052","last_page":"1064"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9968000054359436,"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":0.9968000054359436,"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":0.9959999918937683,"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"}},{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.9958999752998352,"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":0.834081768989563},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7732558250427246},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6459214687347412},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.4819585978984833},{"id":"https://openalex.org/keywords/perspective","display_name":"Perspective (graphical)","score":0.4644807279109955},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.438627153635025},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.43031683564186096},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.4264799654483795}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.834081768989563},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7732558250427246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6459214687347412},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.4819585978984833},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.4644807279109955},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.438627153635025},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.43031683564186096},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.4264799654483795},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","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}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/tip.2023.3238648","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tip.2023.3238648","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:37022079","is_oa":false,"landing_page_url":"https://pubmed.ncbi.nlm.nih.gov/37022079","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":[{"id":"https://metadata.un.org/sdg/15","score":0.5899999737739563,"display_name":"Life in Land"}],"awards":[{"id":"https://openalex.org/G2573920917","display_name":null,"funder_award_id":"62162044","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G3292299456","display_name":null,"funder_award_id":"LSU-KFJJ-2021-05","funder_id":"https://openalex.org/F4320321133","funder_display_name":"Chinese Academy of Sciences"},{"id":"https://openalex.org/G6369404604","display_name":null,"funder_award_id":"61971418","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6871481020","display_name":null,"funder_award_id":"U21A20515","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7090326123","display_name":"\u7f3a\u635f\u6570\u636e\u7684\u9c81\u68d2\u975e\u5b8c\u6574\u591a\u89c6\u56fe\u5b66\u4e60\u65b9\u6cd5\u53ca\u5176\u89c6\u89c9\u5e94\u7528\u7814\u7a76","funder_award_id":"62071157","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8311886428","display_name":null,"funder_award_id":"62171321","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8316038559","display_name":null,"funder_award_id":"62271074","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8432096688","display_name":null,"funder_award_id":"U2003109","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/F4320321133","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35"},{"id":"https://openalex.org/F4320326873","display_name":"National Laboratory of Pattern Recognition","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1903029394","https://openalex.org/W1937812750","https://openalex.org/W2032850818","https://openalex.org/W2124592697","https://openalex.org/W2133228628","https://openalex.org/W2412782625","https://openalex.org/W2503140068","https://openalex.org/W2551751523","https://openalex.org/W2560023338","https://openalex.org/W2563705555","https://openalex.org/W2577537809","https://openalex.org/W2630837129","https://openalex.org/W2735039185","https://openalex.org/W2755226765","https://openalex.org/W2760340275","https://openalex.org/W2787091153","https://openalex.org/W2793461576","https://openalex.org/W2798925380","https://openalex.org/W2799213142","https://openalex.org/W2803946774","https://openalex.org/W2810004461","https://openalex.org/W2883502031","https://openalex.org/W2884436604","https://openalex.org/W2899149423","https://openalex.org/W2899319425","https://openalex.org/W2908320224","https://openalex.org/W2910628332","https://openalex.org/W2946862972","https://openalex.org/W2962749812","https://openalex.org/W2963351448","https://openalex.org/W2963378109","https://openalex.org/W2963881378","https://openalex.org/W2964333009","https://openalex.org/W2967085153","https://openalex.org/W2975194617","https://openalex.org/W3014641072","https://openalex.org/W3018169007","https://openalex.org/W3034427230","https://openalex.org/W3035260401","https://openalex.org/W3084740725","https://openalex.org/W3092462694","https://openalex.org/W3102850314","https://openalex.org/W3105636206","https://openalex.org/W3108948422","https://openalex.org/W3121523901","https://openalex.org/W3130523820","https://openalex.org/W3138516171","https://openalex.org/W3142871063","https://openalex.org/W3165739880","https://openalex.org/W3165745140","https://openalex.org/W3166286626","https://openalex.org/W3170841864","https://openalex.org/W3173787059","https://openalex.org/W3175617055","https://openalex.org/W3184761517","https://openalex.org/W3201514487","https://openalex.org/W3202542211","https://openalex.org/W3203480968","https://openalex.org/W3206476077","https://openalex.org/W3208937872","https://openalex.org/W3213646008","https://openalex.org/W4200444671","https://openalex.org/W4212848489","https://openalex.org/W4214831601","https://openalex.org/W4220813865","https://openalex.org/W4220869836","https://openalex.org/W4223896192","https://openalex.org/W4225668955","https://openalex.org/W4226537900","https://openalex.org/W4285150367","https://openalex.org/W4288277460","https://openalex.org/W4289752563","https://openalex.org/W4293519264","https://openalex.org/W4295936571","https://openalex.org/W4385245566","https://openalex.org/W6739696289","https://openalex.org/W6766844300","https://openalex.org/W6784094891","https://openalex.org/W6797399245","https://openalex.org/W6799579066"],"related_works":["https://openalex.org/W2149537132","https://openalex.org/W641279757","https://openalex.org/W370975646","https://openalex.org/W1670566515","https://openalex.org/W596972243","https://openalex.org/W4242022592","https://openalex.org/W2018871932","https://openalex.org/W69751022","https://openalex.org/W4313230280","https://openalex.org/W1522196789"],"abstract_inverted_index":{"High":[0],"spatial":[1,122],"resolution":[2],"(HSR)":[3],"remote":[4,14,187],"sensing":[5,15,188],"images":[6],"contain":[7],"complex":[8,32],"foreground-background":[9,37],"relationships,":[10],"which":[11,127],"makes":[12],"the":[13,29,49,82,113,119,130,134,148],"land":[16],"cover":[17],"segmentation":[18,22,184,189],"a":[19,61,193],"special":[20],"semantic":[21,183],"task.":[23],"The":[24],"main":[25],"challenges":[26],"come":[27],"from":[28,81],"large-scale":[30],"variation,":[31],"background":[33,97],"samples":[34,154],"and":[35,75,99,115,124,173,186,191,199],"imbalanced":[36],"distribution.":[38],"These":[39],"issues":[40],"make":[41],"recent":[42],"context":[43],"modeling":[44],"methods":[45,185],"sub-optimal":[46],"due":[47],"to":[48,150,160],"lack":[50],"of":[51,84,121,136],"foreground":[52,86,131,138,157],"saliency":[53,87,102,139,158],"modeling.":[54],"To":[55],"handle":[56],"these":[57],"problems,":[58],"we":[59],"propose":[60],"Remote":[62],"Sensing":[63],"Segmentation":[64],"framework":[65],"(RSSFormer),":[66],"including":[67],"Adaptive":[68,90],"TransFormer":[69],"Fusion":[70,92],"Module,":[71],"Detail-aware":[72,109],"Attention":[73,110],"Layer":[74,111],"Foreground":[76,142],"Saliency":[77,143],"Guided":[78,144],"Loss.":[79],"Specifically,":[80],"perspective":[83,135],"relation-based":[85],"modeling,":[88,140],"our":[89,108,141,178],"Transformer":[91],"Module":[93],"can":[94,146],"adaptively":[95],"suppress":[96],"noise":[98],"enhance":[100],"object":[101],"when":[103],"fusing":[104],"multi-scale":[105],"features.":[106],"Then":[107],"extracts":[112],"detail":[114],"foreground-related":[116],"information":[117],"via":[118],"interplay":[120],"attention":[123],"channel":[125],"attention,":[126],"further":[128],"enhances":[129],"saliency.":[132],"From":[133],"optimization-based":[137],"Loss":[145],"guide":[147],"network":[149],"focus":[151],"on":[152,166],"hard":[153],"with":[155],"low":[156],"responses":[159],"achieve":[161],"balanced":[162],"optimization.":[163],"Experimental":[164],"results":[165],"LoveDA":[167],"datasets,":[168,170],"Vaihingen":[169],"Potsdam":[171],"datasets":[172,175],"iSAID":[174],"validate":[176],"that":[177],"method":[179],"outperforms":[180],"existing":[181],"general":[182],"methods,":[190],"achieves":[192],"good":[194],"compromise":[195],"between":[196],"computational":[197],"overhead":[198],"accuracy.":[200],"Our":[201],"code":[202],"is":[203],"available":[204],"at":[205],"https://github.com/Rongtao-Xu/RepresentationLearning/tree/main/RSSFormer-TIP2023.":[206]},"counts_by_year":[{"year":2026,"cited_by_count":22},{"year":2025,"cited_by_count":70},{"year":2024,"cited_by_count":54},{"year":2023,"cited_by_count":26}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
