{"id":"https://openalex.org/W7147121250","doi":"https://doi.org/10.48550/arxiv.2603.27429","title":"Mind the Shape Gap: A Benchmark and Baseline for Deformation-Aware 6D Pose Estimation of Agricultural Produce","display_name":"Mind the Shape Gap: A Benchmark and Baseline for Deformation-Aware 6D Pose Estimation of Agricultural Produce","publication_year":2026,"publication_date":"2026-03-28","ids":{"openalex":"https://openalex.org/W7147121250","doi":"https://doi.org/10.48550/arxiv.2603.27429"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27429","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27429","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.27429","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5132597750","display_name":"Nikolas Chatzis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chatzis, Nikolas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132649694","display_name":"Angeliki Tsinouka","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tsinouka, Angeliki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5054654614","display_name":"Katerina Papadimitriou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Papadimitriou, Katerina","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046941506","display_name":"Niki Efthymiou","orcid":"https://orcid.org/0000-0002-3911-561X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Efthymiou, Niki","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116594340","display_name":"Marios Glytsos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Glytsos, Marios","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021130742","display_name":"George Retsinas","orcid":"https://orcid.org/0000-0001-6734-3575"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Retsinas, George","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5017521265","display_name":"Paris Oikonomou","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oikonomou, Paris","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024184433","display_name":"Gerasimos Potamianos","orcid":"https://orcid.org/0000-0002-9833-7124"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Potamianos, Gerasimos","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132649126","display_name":"Petros Maragos","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Maragos, Petros","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132711494","display_name":"Panagiotis Paraskevas Filntisis","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Filntisis, Panagiotis Paraskevas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10616","display_name":"Smart Agriculture and AI","score":0.30649998784065247,"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":0.30649998784065247,"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/T10653","display_name":"Robot Manipulation and Learning","score":0.18000000715255737,"subfield":{"id":"https://openalex.org/subfields/2207","display_name":"Control and Systems Engineering"},"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.08619999885559082,"subfield":{"id":"https://openalex.org/subfields/2206","display_name":"Computational Mechanics"},"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/pose","display_name":"Pose","score":0.8256999850273132},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.5884000062942505},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.5637000203132629},{"id":"https://openalex.org/keywords/3d-pose-estimation","display_name":"3D pose estimation","score":0.5268999934196472},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.5134000182151794},{"id":"https://openalex.org/keywords/articulated-body-pose-estimation","display_name":"Articulated body pose estimation","score":0.4262999892234802},{"id":"https://openalex.org/keywords/synthetic-data","display_name":"Synthetic data","score":0.3984000086784363}],"concepts":[{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.8256999850273132},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.645799994468689},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6065999865531921},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.5884000062942505},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.5637000203132629},{"id":"https://openalex.org/C36613465","wikidata":"https://www.wikidata.org/wiki/Q4636322","display_name":"3D pose estimation","level":3,"score":0.5268999934196472},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.5134000182151794},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47290000319480896},{"id":"https://openalex.org/C22100474","wikidata":"https://www.wikidata.org/wiki/Q4800952","display_name":"Articulated body pose estimation","level":4,"score":0.4262999892234802},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4099999964237213},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.3984000086784363},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.38580000400543213},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.3849000036716461},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.31520000100135803},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.3091000020503998},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.30000001192092896},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.2865999937057495},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2793999910354614},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.2653999924659729},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27429","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27429","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.27429","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27429","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"score":0.7654715776443481,"id":"https://metadata.un.org/sdg/2","display_name":"Zero hunger"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Accurate":[0],"6D":[1,86,150],"pose":[2,87,151,202],"estimation":[3,203],"for":[4,33,103],"robotic":[5,101],"harvesting":[6],"is":[7,39,196],"fundamentally":[8],"hindered":[9],"by":[10,131],"the":[11,56,60,81,123,175],"biological":[12],"deformability":[13],"and":[14,76,88,141,152],"high":[15,104],"intra-class":[16],"shape":[17,194],"variability":[18],"of":[19,37,68,78,127,139,184],"agricultural":[20,205],"produce.":[21,129],"Instance-level":[22],"methods":[23,113],"fail":[24],"in":[25,204],"this":[26,132],"setting,":[27],"as":[28],"obtaining":[29],"exact":[30],"3D":[31,90],"models":[32],"every":[34],"unique":[35],"piece":[36],"produce":[38,96,162],"practically":[40],"infeasible,":[41],"while":[42],"category-level":[43],"approaches":[44],"that":[45,111,147,192],"rely":[46],"on":[47,166,181],"a":[48,100,143,157,197],"fixed":[49],"template":[50],"suffer":[51,114],"significant":[52],"accuracy":[53],"degradation":[54,119],"when":[55,120],"prior":[57],"deviates":[58],"from":[59,156],"true":[61],"instance":[62],"geometry.":[63],"To":[64],"bridge":[65],"such":[66],"lack":[67],"robustness":[69],"to":[70,116],"deformation,":[71],"we":[72,109,134],"introduce":[73],"PEAR":[74],"(Pose":[75],"dEformation":[77],"Agricultural":[79],"pRoduce),":[80],"first":[82],"benchmark":[83],"providing":[84],"joint":[85],"per-instance":[89],"deformation":[91],"ground":[92],"truth":[93],"across":[94,160],"8":[95,185],"categories,":[97],"acquired":[98],"via":[99],"manipulator":[102],"annotation":[105],"accuracy.":[106],"Using":[107],"PEAR,":[108],"show":[110],"state-of-the-art":[112],"up":[115],"6x":[117],"performance":[118],"faced":[121],"with":[122,169],"inherent":[124],"geometric":[125],"deviations":[126],"real-world":[128],"Motivated":[130],"finding,":[133],"propose":[135],"SEED":[136,178],"(Simultaneous":[137],"Estimation":[138],"posE":[140],"Deformation),":[142],"unified":[144],"RGB-only":[145,189],"framework":[146],"jointly":[148],"predicts":[149],"explicit":[153,193],"lattice":[154],"deformations":[155],"single":[158],"image":[159],"multiple":[161],"categories.":[163],"Trained":[164],"entirely":[165],"synthetic":[167],"data":[168],"generative":[170],"texture":[171],"augmentation":[172],"applied":[173],"at":[174],"UV":[176],"level,":[177],"outperforms":[179],"MegaPose":[180],"6":[182],"out":[183],"categories":[186],"under":[187],"identical":[188],"conditions,":[190],"demonstrating":[191],"modeling":[195],"critical":[198],"step":[199],"toward":[200],"reliable":[201],"robotics.":[206]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-04-02T00:00:00"}
