{"id":"https://openalex.org/W4401907554","doi":"https://doi.org/10.1109/tgrs.2024.3450732","title":"PMHO: Point-Supervised Oriented Object Detection Based on Segmentation-Driven Proposal Generation","display_name":"PMHO: Point-Supervised Oriented Object Detection Based on Segmentation-Driven Proposal Generation","publication_year":2024,"publication_date":"2024-01-01","ids":{"openalex":"https://openalex.org/W4401907554","doi":"https://doi.org/10.1109/tgrs.2024.3450732"},"language":"en","primary_location":{"id":"doi:10.1109/tgrs.2024.3450732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3450732","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/A5101557084","display_name":"Shun Zhang","orcid":"https://orcid.org/0000-0003-3380-8957"},"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":"Shun Zhang","raw_affiliation_strings":["School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5037834773","display_name":"Jihui Long","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":"Jihui Long","raw_affiliation_strings":["School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062972478","display_name":"Yaohui Xu","orcid":"https://orcid.org/0000-0001-8083-8767"},"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":"Yaohui Xu","raw_affiliation_strings":["School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5067207818","display_name":"Shaohui Mei","orcid":"https://orcid.org/0000-0002-8018-596X"},"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":"Shaohui Mei","raw_affiliation_strings":["School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China"],"affiliations":[{"raw_affiliation_string":"School of Electronic and Information, Northwestern Polytechnical University, Xi’an, Shaanxi, China","institution_ids":["https://openalex.org/I17145004"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101557084"],"corresponding_institution_ids":["https://openalex.org/I17145004"],"apc_list":null,"apc_paid":null,"fwci":3.49,"has_fulltext":false,"cited_by_count":14,"citation_normalized_percentile":{"value":0.93920935,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"62","issue":null,"first_page":"1","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9998000264167786,"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":0.9950000047683716,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9936000108718872,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/segmentation","display_name":"Segmentation","score":0.6721396446228027},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6709764003753662},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5910869836807251},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5780549049377441},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.5553973317146301},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.538602352142334},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.4980630874633789},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4617123603820801},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3852635324001312},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.33073437213897705},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.12071961164474487},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08412539958953857}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6721396446228027},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6709764003753662},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5910869836807251},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5780549049377441},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.5553973317146301},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.538602352142334},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.4980630874633789},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4617123603820801},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3852635324001312},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.33073437213897705},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.12071961164474487},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08412539958953857},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/tgrs.2024.3450732","is_oa":false,"landing_page_url":"https://doi.org/10.1109/tgrs.2024.3450732","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/G5521239382","display_name":null,"funder_award_id":"62171381","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6393876729","display_name":null,"funder_award_id":"62271409","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":65,"referenced_works":["https://openalex.org/W639708223","https://openalex.org/W2108598243","https://openalex.org/W2144506857","https://openalex.org/W2194775991","https://openalex.org/W2593539516","https://openalex.org/W2604260814","https://openalex.org/W2608567823","https://openalex.org/W2962749812","https://openalex.org/W2963351448","https://openalex.org/W2963603913","https://openalex.org/W2964979676","https://openalex.org/W2972052070","https://openalex.org/W2982770724","https://openalex.org/W2991359031","https://openalex.org/W2992240579","https://openalex.org/W3092088889","https://openalex.org/W3092663126","https://openalex.org/W3094567318","https://openalex.org/W3106228955","https://openalex.org/W3107075539","https://openalex.org/W3107730255","https://openalex.org/W3109055651","https://openalex.org/W3140922383","https://openalex.org/W3152083889","https://openalex.org/W3152635971","https://openalex.org/W3158568413","https://openalex.org/W3164897814","https://openalex.org/W3165312683","https://openalex.org/W3170033848","https://openalex.org/W3180169285","https://openalex.org/W3181729304","https://openalex.org/W3198296433","https://openalex.org/W3214677295","https://openalex.org/W4213452156","https://openalex.org/W4214648418","https://openalex.org/W4226359564","https://openalex.org/W4229002315","https://openalex.org/W4280496735","https://openalex.org/W4285293152","https://openalex.org/W4285820611","https://openalex.org/W4288365527","https://openalex.org/W4312322023","https://openalex.org/W4312578467","https://openalex.org/W4312611884","https://openalex.org/W4312792327","https://openalex.org/W4313141979","https://openalex.org/W4313476697","https://openalex.org/W4320002812","https://openalex.org/W4321488138","https://openalex.org/W4324116440","https://openalex.org/W4365790486","https://openalex.org/W4388740367","https://openalex.org/W4389890901","https://openalex.org/W4390874575","https://openalex.org/W4402754222","https://openalex.org/W4402754284","https://openalex.org/W6757817989","https://openalex.org/W6784164614","https://openalex.org/W6788870397","https://openalex.org/W6789615881","https://openalex.org/W6796744688","https://openalex.org/W6846169171","https://openalex.org/W6852044425","https://openalex.org/W6858292983","https://openalex.org/W6873344623"],"related_works":["https://openalex.org/W4379231730","https://openalex.org/W4389858081","https://openalex.org/W2737719445","https://openalex.org/W4239098401","https://openalex.org/W2501551404","https://openalex.org/W4385583601","https://openalex.org/W4298131179","https://openalex.org/W1522196789","https://openalex.org/W4292830139","https://openalex.org/W4319309705"],"abstract_inverted_index":{"Oriented":[0],"object":[1,44,82,88,209],"detection":[2,83],"has":[3],"gained":[4],"increasing":[5],"attention":[6],"due":[7],"to":[8,11,104,118,129,169,217],"its":[9],"ability":[10],"detect":[12],"objects":[13],"with":[14,188],"arbitrary":[15],"orientations":[16],"in":[17,59],"the":[18,26,94,98,106,120,131,143,146,163,207,219,226],"field":[19],"of":[20,29,152,165,179],"remote":[21],"sensing":[22],"(RS)":[23],"images.":[24],"However,":[25],"laborious":[27],"task":[28],"annotating":[30],"oriented":[31,81,208],"bounding":[32,52],"boxes":[33,53],"(OBBs)":[34],"presents":[35],"significant":[36,65],"challenges":[37],"for":[38,156,162,173],"training":[39],"a":[40,73,113,124,153,184,195,200],"fully":[41],"supervised":[42,57,80],"arbitrary-oriented":[43],"detector.":[45],"Some":[46],"existing":[47],"approaches":[48],"apply":[49],"annotated":[50,100],"horizontal":[51],"(HBBs)":[54],"as":[55,102],"weakly":[56,79],"signals,":[58],"which":[60,150,248],"even":[61],"HBB":[62],"annotations":[63],"require":[64],"human":[66],"efforts.":[67],"In":[68],"this":[69],"article,":[70],"we":[71,91,182],"propose":[72],"point-to-mask-to-HBB-to-OBB":[74],"(PMHO)":[75],"method":[76,252],"that":[77,250],"achieves":[78,253],"by":[84,194],"requiring":[85],"only":[86],"single-point":[87],"annotations.":[89],"Specifically,":[90],"first":[92],"take":[93],"input":[95],"images":[96],"and":[97,110,123,137,158,225,237,245],"given":[99,227],"points":[101],"prompts":[103],"obtain":[105],"initial":[107],"segmentation":[108],"masks,":[109],"then":[111],"present":[112,183],"neighboring":[114],"mask":[115,126,144],"combination":[116],"scheme":[117],"address":[119],"over-segmentation":[121],"issue":[122],"point-centric":[125],"selection":[127],"strategy":[128,187],"filtrate":[130],"related":[132],"masks.":[133],"Based":[134],"on":[135,191,199,242],"positive":[136],"negative":[138],"proposal":[139],"bags":[140],"transferred":[141],"from":[142],"regions,":[145],"pseudo-HBB":[147,185,235],"generation":[148],"network":[149],"consists":[151],"classification":[154,157],"branch":[155,161],"an":[159,211],"instance":[160],"localization":[164],"individual":[166],"proposals,":[167],"aims":[168],"generate":[170],"pseudo":[171,180,228],"HBBs":[172],"each":[174],"object.":[175],"For":[176],"further":[177],"refinement":[178],"HBBs,":[181],"filtering":[186],"K-means":[189],"clustering":[190],"features":[192],"extracted":[193],"CNN":[196],"model":[197],"pretrained":[198],"large-scale":[201],"offline":[202],"RS":[203],"dataset.":[204],"To":[205],"train":[206],"detector,":[210],"inscribed":[212],"ellipse":[213],"constraint":[214],"is":[215],"proposed":[216],"measure":[218],"regression":[220],"loss":[221],"between":[222],"predicted":[223],"OBBs":[224],"HBBs.":[229],"Extensive":[230],"experiments":[231],"including":[232],"OBB":[233],"detection,":[234],"generation,":[236],"ablation":[238],"studies":[239],"are":[240],"conducted":[241],"public":[243],"DIOR":[244],"DIOR-R":[246],"datasets,":[247],"demonstrates":[249],"our":[251],"state-of-the-art":[254],"performance.":[255]},"counts_by_year":[{"year":2025,"cited_by_count":8},{"year":2024,"cited_by_count":6}],"updated_date":"2026-03-27T05:58:40.876381","created_date":"2025-10-10T00:00:00"}