{"id":"https://openalex.org/W4406322219","doi":"https://doi.org/10.1109/tgrs.2025.3529031","title":"PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images","display_name":"PointSAM: Pointly-Supervised Segment Anything Model for Remote Sensing Images","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W4406322219","doi":"https://doi.org/10.1109/tgrs.2025.3529031"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2025.3529031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3529031","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/A5072832353","display_name":"Nanqing Liu","orcid":"https://orcid.org/0000-0001-7564-4896"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Nanqing Liu","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0001-7564-4896","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100451925","display_name":"Xun Xu","orcid":"https://orcid.org/0000-0002-5220-2240"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Xun Xu","raw_affiliation_strings":["I2R, A&#x002A;STAR, North Tower, Singapore"],"raw_orcid":"https://orcid.org/0000-0002-5220-2240","affiliations":[{"raw_affiliation_string":"I2R, A&#x002A;STAR, North Tower, Singapore","institution_ids":["https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5007736768","display_name":"Yongyi Su","orcid":"https://orcid.org/0009-0001-6911-8256"},"institutions":[{"id":"https://openalex.org/I115228651","display_name":"Agency for Science, Technology and Research","ror":"https://ror.org/036wvzt09","country_code":"SG","type":"government","lineage":["https://openalex.org/I115228651"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Yongyi Su","raw_affiliation_strings":["I2R, A&#x002A;STAR, North Tower, Singapore"],"raw_orcid":"https://orcid.org/0009-0001-6911-8256","affiliations":[{"raw_affiliation_string":"I2R, A&#x002A;STAR, North Tower, Singapore","institution_ids":["https://openalex.org/I115228651"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100707830","display_name":"Haojie Zhang","orcid":"https://orcid.org/0000-0002-4577-3600"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haojie Zhang","raw_affiliation_strings":["School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5015155189","display_name":"Heng-Chao Li","orcid":"https://orcid.org/0000-0002-9735-570X"},"institutions":[{"id":"https://openalex.org/I4800084","display_name":"Southwest Jiaotong University","ror":"https://ror.org/00hn7w693","country_code":"CN","type":"education","lineage":["https://openalex.org/I4800084"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heng-Chao Li","raw_affiliation_strings":["School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China"],"raw_orcid":"https://orcid.org/0000-0002-9735-570X","affiliations":[{"raw_affiliation_string":"School of Information Science and Technology, Southwest Jiaotong University, Chengdu, China","institution_ids":["https://openalex.org/I4800084"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":32.0024,"has_fulltext":false,"cited_by_count":42,"citation_normalized_percentile":{"value":0.99792414,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":99,"max":100},"biblio":{"volume":"63","issue":null,"first_page":"1","last_page":"15"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.982200026512146,"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"}},"topics":[{"id":"https://openalex.org/T10689","display_name":"Remote-Sensing Image Classification","score":0.982200026512146,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9728000164031982,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13282","display_name":"Automated Road and Building Extraction","score":0.9452000260353088,"subfield":{"id":"https://openalex.org/subfields/2212","display_name":"Ocean 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/remote-sensing","display_name":"Remote sensing","score":0.6637598276138306},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6172733902931213},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3578510582447052},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3567157983779907},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.26028627157211304}],"concepts":[{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.6637598276138306},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6172733902931213},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3578510582447052},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3567157983779907},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.26028627157211304}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2025.3529031","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2025.3529031","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/G4543526808","display_name":null,"funder_award_id":"23NSFSC0030","funder_id":"https://openalex.org/F4320329861","funder_display_name":"Natural Science Foundation of Sichuan Province"},{"id":"https://openalex.org/G7436548981","display_name":null,"funder_award_id":"62106078","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G7509836859","display_name":null,"funder_award_id":"62271418","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G8519419943","display_name":null,"funder_award_id":"CSC202207000056","funder_id":"https://openalex.org/F4320322725","funder_display_name":"China Scholarship Council"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320322725","display_name":"China Scholarship Council","ror":"https://ror.org/04atp4p48"},{"id":"https://openalex.org/F4320329861","display_name":"Natural Science Foundation of Sichuan Province","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":81,"referenced_works":["https://openalex.org/W607748843","https://openalex.org/W611457968","https://openalex.org/W2512351403","https://openalex.org/W2908320224","https://openalex.org/W2967487473","https://openalex.org/W2982673782","https://openalex.org/W2982770724","https://openalex.org/W3035524453","https://openalex.org/W3038948729","https://openalex.org/W3091002423","https://openalex.org/W3096609285","https://openalex.org/W3109055651","https://openalex.org/W3135324481","https://openalex.org/W3172507542","https://openalex.org/W3201018943","https://openalex.org/W3211547284","https://openalex.org/W4285179303","https://openalex.org/W4312322023","https://openalex.org/W4312792327","https://openalex.org/W4313013233","https://openalex.org/W4313476697","https://openalex.org/W4367276728","https://openalex.org/W4385574797","https://openalex.org/W4386066721","https://openalex.org/W4386076342","https://openalex.org/W4387828790","https://openalex.org/W4388129777","https://openalex.org/W4388624446","https://openalex.org/W4388676554","https://openalex.org/W4389430914","https://openalex.org/W4390872703","https://openalex.org/W4390874575","https://openalex.org/W4391021462","https://openalex.org/W4391109864","https://openalex.org/W4391128373","https://openalex.org/W4391304743","https://openalex.org/W4391991763","https://openalex.org/W4392251629","https://openalex.org/W4392719505","https://openalex.org/W4393972808","https://openalex.org/W4394706539","https://openalex.org/W4399426542","https://openalex.org/W4400229979","https://openalex.org/W4400350735","https://openalex.org/W4401907554","https://openalex.org/W4402260002","https://openalex.org/W4402727760","https://openalex.org/W4402754211","https://openalex.org/W4402754222","https://openalex.org/W4402754284","https://openalex.org/W4403095713","https://openalex.org/W4403977314","https://openalex.org/W4404199191","https://openalex.org/W6620707391","https://openalex.org/W6687400500","https://openalex.org/W6755207826","https://openalex.org/W6778883912","https://openalex.org/W6788125050","https://openalex.org/W6789505266","https://openalex.org/W6790019176","https://openalex.org/W6791353385","https://openalex.org/W6796581206","https://openalex.org/W6796744688","https://openalex.org/W6845709062","https://openalex.org/W6846169171","https://openalex.org/W6851641870","https://openalex.org/W6851980744","https://openalex.org/W6852044425","https://openalex.org/W6852909635","https://openalex.org/W6854362512","https://openalex.org/W6854481535","https://openalex.org/W6857547394","https://openalex.org/W6859634743","https://openalex.org/W6860096759","https://openalex.org/W6860365250","https://openalex.org/W6860844317","https://openalex.org/W6861232000","https://openalex.org/W6870839691","https://openalex.org/W6872474088","https://openalex.org/W6874047301","https://openalex.org/W6874990969"],"related_works":["https://openalex.org/W2772917594","https://openalex.org/W2036807459","https://openalex.org/W2058170566","https://openalex.org/W2755342338","https://openalex.org/W2166024367","https://openalex.org/W3116076068","https://openalex.org/W2229312674","https://openalex.org/W2951359407","https://openalex.org/W2079911747","https://openalex.org/W1969923398"],"abstract_inverted_index":{"Segment":[0],"anything":[1],"model":[2,8,41],"(SAM)":[3],"is":[4,13,236],"an":[5],"advanced":[6],"foundational":[7],"for":[9,132,219,230],"image":[10],"segmentation,":[11],"which":[12],"gradually":[14],"being":[15],"applied":[16],"to":[17,23,105,112,135,169],"remote":[18],"sensing":[19],"images":[20],"(RSIs).":[21],"Due":[22],"the":[24,101,109,116,155],"domain":[25],"gap":[26],"between":[27],"RSIs":[28,121],"and":[29,42,61,103,125,192,206,226],"natural":[30],"images,":[31],"traditional":[32],"methods":[33],"typically":[34],"use":[35],"SAM":[36,57,180],"as":[37,140,166,215],"a":[38,71,147,177,216],"source":[39],"pretrained":[40],"fine-tune":[43],"it":[44,130],"with":[45,203],"fully":[46],"supervised":[47],"masks.":[48],"Unlike":[49],"these":[50,173],"methods,":[51],"our":[52,197],"work":[53],"focuses":[54],"on":[55,154,185],"fine-tuning":[56],"using":[58,108],"more":[59],"convenient":[60],"challenging":[62],"point":[63,133],"annotations.":[64],"Leveraging":[65],"SAM\u2019s":[66],"zero-shot":[67],"capability,":[68],"we":[69,90,145,175],"adopt":[70],"self-training":[72],"framework":[73],"that":[74,196],"iteratively":[75],"generates":[76],"pseudolabels.":[77],"However,":[78],"noisy":[79],"labels":[80],"in":[81,115],"pseudolabels":[82],"can":[83,213],"cause":[84],"error":[85],"accumulation.":[86],"To":[87,142],"address":[88],"this,":[89,144],"introduce":[91],"prototype-based":[92],"regularization":[93],"(PBR),":[94],"where":[95,161],"target":[96],"prototypes":[97,107],"are":[98,164],"extracted":[99],"from":[100],"dataset":[102],"matched":[104],"predicted":[106],"Hungarian":[110],"algorithm":[111],"guide":[113],"learning":[114],"correct":[117],"direction.":[118],"In":[119,210],"addition,":[120,211],"have":[122],"complex":[123],"backgrounds":[124],"densely":[126],"packed":[127],"objects,":[128],"making":[129],"possible":[131],"prompts":[134],"mistakenly":[136],"group":[137],"multiple":[138],"objects":[139],"one.":[141],"resolve":[143],"propose":[146],"negative":[148,167],"prompt":[149],"calibration":[150],"(NPC)":[151],"method":[152,198],"based":[153],"nonoverlapping":[156],"nature":[157],"of":[158],"instance":[159],"masks,":[160],"overlapping":[162],"masks":[163],"used":[165],"signals":[168],"refine":[170],"segmentation.":[171],"Combining":[172],"techniques,":[174],"present":[176],"novel":[178],"pointly-supervised":[179],"(PointSAM).":[181],"We":[182],"conduct":[183],"experiments":[184],"three":[186],"RSI":[187],"datasets,":[188],"including":[189],"WHU,":[190],"HRSID,":[191],"NWPU":[193],"VHR-10,":[194],"showing":[195],"significantly":[199],"outperforms":[200],"direct":[201],"testing":[202],"SAM,":[204],"SAM2,":[205],"other":[207,231],"comparison":[208],"methods.":[209],"PointSAM":[212],"act":[214],"point-to-box":[217],"converter":[218],"oriented":[220],"object":[221],"detection,":[222],"achieving":[223],"promising":[224],"results":[225],"indicating":[227],"its":[228],"potential":[229],"point-supervised":[232],"tasks.":[233],"The":[234],"code":[235],"available":[237],"at":[238],"<uri":[239],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[240],"xmlns:xlink=\"http://www.w3.org/1999/xlink\">https://github.com/Lans1ng/PointSAM</uri>.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":7},{"year":2025,"cited_by_count":35}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}