{"id":"https://openalex.org/W7124422198","doi":"https://doi.org/10.1109/jstsp.2026.3654362","title":"DepthCropSeg++: Scaling a Crop Segmentation Foundation Model With Depth-Labeled Data","display_name":"DepthCropSeg++: Scaling a Crop Segmentation Foundation Model With Depth-Labeled Data","publication_year":2026,"publication_date":"2026-01-15","ids":{"openalex":"https://openalex.org/W7124422198","doi":"https://doi.org/10.1109/jstsp.2026.3654362"},"language":null,"primary_location":{"id":"doi:10.1109/jstsp.2026.3654362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2026.3654362","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2601.12366","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5085469102","display_name":"Jiafei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jiafei Zhang","raw_affiliation_strings":["MetaPheno Laboratory, Shanghai, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"MetaPheno Laboratory, Shanghai, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":null,"display_name":"Songliang Cao","orcid":"https://orcid.org/0009-0001-1692-5505"},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Songliang Cao","raw_affiliation_strings":["National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0009-0001-1692-5505","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103115488","display_name":"Binghui Xu","orcid":"https://orcid.org/0000-0002-9315-9269"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Binghui Xu","raw_affiliation_strings":["Wuhan Digital Engineering Institute, Wuhan, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Wuhan Digital Engineering Institute, Wuhan, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123191713","display_name":"Yanan Li","orcid":null},"institutions":[{"id":"https://openalex.org/I91125648","display_name":"Wuhan Institute of Technology","ror":"https://ror.org/04jcykh16","country_code":"CN","type":"education","lineage":["https://openalex.org/I91125648"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yanan Li","raw_affiliation_strings":["Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, School of Artificial Intelligence, Wuhan Institute of Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-4259-994X","affiliations":[{"raw_affiliation_string":"Hubei Key Laboratory of Intelligent Robot, School of Computer Science and Engineering, School of Artificial Intelligence, Wuhan Institute of Technology, Wuhan, China","institution_ids":["https://openalex.org/I91125648"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123199795","display_name":"Weiwei Jia","orcid":null},"institutions":[{"id":"https://openalex.org/I4210098421","display_name":"Beijing Agricultural Machinery Research Institute","ror":"https://ror.org/010znyz59","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210098421"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weiwei Jia","raw_affiliation_strings":["Beijing Agricultural Technology Extension Station, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Agricultural Technology Extension Station, Beijing, China","institution_ids":["https://openalex.org/I4210098421"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123229307","display_name":"Tingting Wu","orcid":null},"institutions":[{"id":"https://openalex.org/I89652312","display_name":"Northwest A&F University","ror":"https://ror.org/0051rme32","country_code":"CN","type":"education","lineage":["https://openalex.org/I89652312"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tingting Wu","raw_affiliation_strings":["College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling, China"],"raw_orcid":"https://orcid.org/0009-0005-0738-8372","affiliations":[{"raw_affiliation_string":"College of Mechanical and Electronic Engineering, Northwest A&amp;F University, Yangling, China","institution_ids":["https://openalex.org/I89652312"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103414853","display_name":"H. H. Lu","orcid":null},"institutions":[{"id":"https://openalex.org/I47720641","display_name":"Huazhong University of Science and Technology","ror":"https://ror.org/00p991c53","country_code":"CN","type":"education","lineage":["https://openalex.org/I47720641"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hao Lu","raw_affiliation_strings":["National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0003-3854-8664","affiliations":[{"raw_affiliation_string":"National Key Laboratory of Multispectral Information Intelligent Processing Technology, School of Artificial Intelligence and Automation, Huazhong University of Science and Technology, Wuhan, China","institution_ids":["https://openalex.org/I47720641"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5113848968","display_name":"Weijuan Hu","orcid":"https://orcid.org/0000-0001-7332-9200"},"institutions":[{"id":"https://openalex.org/I4210124606","display_name":"Institute of Genetics and Developmental Biology","ror":"https://ror.org/02aee5m12","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210124606"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weijuan Hu","raw_affiliation_strings":["Laboratory of Advanced Breeding Technologies, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-7332-9200","affiliations":[{"raw_affiliation_string":"Laboratory of Advanced Breeding Technologies, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing, China","institution_ids":["https://openalex.org/I4210124606"]}]},{"author_position":"last","author":{"id":null,"display_name":"Zhiguo Han","orcid":"https://orcid.org/0000-0001-9974-3258"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhiguo Han","raw_affiliation_strings":["MetaPheno Laboratory, Shanghai, China"],"raw_orcid":"https://orcid.org/0000-0001-9974-3258","affiliations":[{"raw_affiliation_string":"MetaPheno Laboratory, Shanghai, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":8.3667,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.93085218,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":97},"biblio":{"volume":"20","issue":"2","first_page":"129","last_page":"141"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},"topics":[{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.9628000259399414,"subfield":{"id":"https://openalex.org/subfields/1110","display_name":"Plant Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.01889999955892563,"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.004999999888241291,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.7236999869346619},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.5133000016212463},{"id":"https://openalex.org/keywords/image-segmentation","display_name":"Image segmentation","score":0.47269999980926514},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.36890000104904175},{"id":"https://openalex.org/keywords/precision-agriculture","display_name":"Precision agriculture","score":0.3684999942779541},{"id":"https://openalex.org/keywords/market-segmentation","display_name":"Market segmentation","score":0.3375000059604645}],"concepts":[{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.7236999869346619},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.699999988079071},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6182000041007996},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5181999802589417},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.5133000016212463},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.47269999980926514},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.36890000104904175},{"id":"https://openalex.org/C120217122","wikidata":"https://www.wikidata.org/wiki/Q740083","display_name":"Precision agriculture","level":3,"score":0.3684999942779541},{"id":"https://openalex.org/C125308379","wikidata":"https://www.wikidata.org/wiki/Q363057","display_name":"Market segmentation","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.31949999928474426},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30649998784065247},{"id":"https://openalex.org/C110384440","wikidata":"https://www.wikidata.org/wiki/Q1143270","display_name":"Upsampling","level":3,"score":0.30230000615119934},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.2994000017642975},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2915000021457672},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.29100000858306885},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.26829999685287476}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/jstsp.2026.3654362","is_oa":false,"landing_page_url":"https://doi.org/10.1109/jstsp.2026.3654362","pdf_url":null,"source":{"id":"https://openalex.org/S42167783","display_name":"IEEE Journal of Selected Topics in Signal Processing","issn_l":"1932-4553","issn":["1932-4553","1941-0484"],"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 Journal of Selected Topics in Signal Processing","raw_type":"journal-article"},{"id":"pmh:oai:arXiv.org:2601.12366","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.12366","pdf_url":"https://arxiv.org/pdf/2601.12366","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2601.12366","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2601.12366","pdf_url":"https://arxiv.org/pdf/2601.12366","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/2","score":0.6938920617103577,"display_name":"Zero hunger"}],"awards":[{"id":"https://openalex.org/G5315503482","display_name":null,"funder_award_id":"32370435","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"We":[0,143],"introduce":[1],"DepthCropSeg++,":[2],"a":[3,22,50,126,147,168,203,266],"foundation":[4,48,214],"model":[5,72,166,175,235],"for":[6,25,159,272],"crop":[7,13,79,99,121,130,190,258,273],"segmentation,":[8,122],"capable":[9],"of":[10,47,52,111,269],"segmenting":[11],"different":[12],"species":[14,138],"under":[15,97],"open":[16],"in-field":[17],"environment.":[18,103],"Crop":[19],"segmentation":[20,80,131,150],"is":[21],"fundamental":[23],"task":[24],"modern":[26],"agriculture,":[27],"which":[28],"closely":[29],"relates":[30],"to":[31,70,88,120,123,181],"many":[32],"downstream":[33],"tasks":[34],"such":[35],"as":[36],"plant":[37],"phenotyping,":[38],"density":[39],"estimation,":[40],"and":[41,56,74,128,139,163,185,211,228,256],"weed":[42],"control.":[43],"In":[44,104],"the":[45,109,165,183,270],"era":[46],"models,":[49],"number":[51],"generic":[53],"large":[54],"language":[55],"vision":[57,213],"models":[58,63,81,215],"have":[59,64],"been":[60],"developed.":[61],"These":[62],"demonstrated":[65],"remarkable":[66],"realworld":[67],"generalization":[68,186],"due":[69,87],"significant":[71,222],"capacity":[73],"largescale":[75],"datasets.":[76,191],"However,":[77],"current":[78],"mostly":[82],"learn":[83],"from":[84],"limited":[85],"data":[86],"expensive":[89],"pixel-level":[90],"labelling":[91],"cost,":[92],"often":[93],"performing":[94],"well":[95],"only":[96],"specific":[98],"types":[100],"or":[101],"controlled":[102],"this":[105],"work,":[106],"we":[107,177],"follow":[108],"vein":[110],"our":[112],"previous":[113],"work":[114],"DepthCropSeg,":[115],"an":[116],"almost":[117],"unsupervised":[118],"approach":[119],"scale":[124],"up":[125],"cross-species":[127],"crossscene":[129],"dataset,":[132],"with":[133,156,167],"28,406":[134],"images":[135],"across":[136,188],"30+":[137],"15":[140],"environmental":[141],"conditions.":[142],"also":[144],"build":[145],"upon":[146],"state-of-the-art":[148],"semantic":[149],"architecture":[151],"ViT-Adapter":[152],"architecture,":[153],"enhance":[154],"it":[155],"dynamic":[157],"upsampling":[158],"improved":[160],"detail":[161],"awareness,":[162],"train":[164],"two-stage":[169],"selftraining":[170],"pipeline.":[171],"To":[172],"systematically":[173],"validate":[174],"performance,":[176],"conduct":[178],"comprehensive":[179,204],"experiments":[180],"justify":[182],"effectiveness":[184],"capabilities":[187],"multiple":[189],"Results":[192],"demonstrate":[193],"that":[194],"DepthCropSeg++":[195],"achieves":[196],"<inline-formula":[197],"xmlns:mml=\"http://www.w3.org/1998/Math/MathML\"":[198,225,230,245,252,261],"xmlns:xlink=\"http://www.w3.org/1999/xlink\"><tex-math":[199,226,231,246,253,262],"notation=\"LaTeX\">$93.11\\%$</tex-math></inline-formula>":[200],"mIoU":[201],"on":[202],"testing":[205],"set,":[206],"outperforming":[207],"both":[208],"supervised":[209],"baselines":[210],"general-purpose":[212],"like":[216],"Segmentation":[217],"Anything":[218],"Model":[219],"(SAM)":[220],"by":[221],"margins":[223],"(<inline-formula":[224,244,251,260],"notation=\"LaTeX\">$+0.36\\%$</tex-math></inline-formula>":[227],"+<inline-formula":[229],"notation=\"LaTeX\">$48.57\\%$</tex-math></inline-formula>":[232],"respectively).":[233],"The":[234],"particularly":[236],"excels":[237],"in":[238],"challenging":[239],"scenarios":[240],"including":[241],"night-time":[242],"environment":[243],"notation=\"LaTeX\">$86.90\\%$</tex-math></inline-formula>":[247],"mIoU),":[248,255,264],"high-density":[249],"canopies":[250],"notation=\"LaTeX\">$90.09\\%$</tex-math></inline-formula>":[254,263],"unseen":[257],"varieties":[259],"indicating":[265],"new":[267],"state":[268],"art":[271],"segmentation.":[274]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-07-03T08:13:44.112507","created_date":"2026-01-17T00:00:00"}