{"id":"https://openalex.org/W7147275260","doi":"https://doi.org/10.48550/arxiv.2603.27773","title":"RINO: Rotation-Invariant Non-Rigid Correspondences","display_name":"RINO: Rotation-Invariant Non-Rigid Correspondences","publication_year":2026,"publication_date":"2026-03-29","ids":{"openalex":"https://openalex.org/W7147275260","doi":"https://doi.org/10.48550/arxiv.2603.27773"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.27773","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27773","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.27773","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5022094171","display_name":"Maolin Gao","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gao, Maolin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132679051","display_name":"Shao Jie Hu-Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu-Chen, Shao Jie","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5127804448","display_name":"Congyue Deng","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Deng, Congyue","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132683678","display_name":"Riccardo Marin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Marin, Riccardo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5132706588","display_name":"Leonidas Guibas","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guibas, Leonidas","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5132703825","display_name":"Daniel Cremers","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cremers, Daniel","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5022094171"],"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9473000168800354,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9473000168800354,"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"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.01549999974668026,"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"}},{"id":"https://openalex.org/T11448","display_name":"Face recognition and analysis","score":0.002199999988079071,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.54830002784729},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.5163999795913696},{"id":"https://openalex.org/keywords/computer-graphics","display_name":"Computer graphics","score":0.5101000070571899},{"id":"https://openalex.org/keywords/correspondence-problem","display_name":"Correspondence problem","score":0.4853000044822693},{"id":"https://openalex.org/keywords/limiting","display_name":"Limiting","score":0.4702000021934509},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4065999984741211},{"id":"https://openalex.org/keywords/graphics","display_name":"Graphics","score":0.38589999079704285},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3797000050544739},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.3781000077724457}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7128000259399414},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6585000157356262},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.54830002784729},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.5163999795913696},{"id":"https://openalex.org/C77660652","wikidata":"https://www.wikidata.org/wiki/Q150971","display_name":"Computer graphics","level":2,"score":0.5101000070571899},{"id":"https://openalex.org/C3004257","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Correspondence problem","level":2,"score":0.4853000044822693},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.47099998593330383},{"id":"https://openalex.org/C188198153","wikidata":"https://www.wikidata.org/wiki/Q1613840","display_name":"Limiting","level":2,"score":0.4702000021934509},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4065999984741211},{"id":"https://openalex.org/C21442007","wikidata":"https://www.wikidata.org/wiki/Q1027879","display_name":"Graphics","level":2,"score":0.38589999079704285},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3797000050544739},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.3781000077724457},{"id":"https://openalex.org/C2164484","wikidata":"https://www.wikidata.org/wiki/Q5170150","display_name":"Core (optical fiber)","level":2,"score":0.3619999885559082},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.3506999909877777},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3061999976634979},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.29260000586509705},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.28780001401901245},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C117978034","wikidata":"https://www.wikidata.org/wiki/Q5422192","display_name":"Extractor","level":2,"score":0.27880001068115234},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.26820001006126404},{"id":"https://openalex.org/C112604564","wikidata":"https://www.wikidata.org/wiki/Q7489226","display_name":"Shape analysis (program analysis)","level":3,"score":0.26170000433921814},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.2599000036716461},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.2515000104904175}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.27773","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27773","pdf_url":null,"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":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.27773","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.27773","pdf_url":null,"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":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Dense":[0],"3D":[1],"shape":[2,57,102],"correspondence":[3,49],"remains":[4],"a":[5,68,92],"central":[6],"challenge":[7],"in":[8],"computer":[9],"vision":[10],"and":[11,35,55,125],"graphics":[12],"as":[13],"many":[14],"deep":[15],"learning":[16,75],"approaches":[17],"still":[18],"rely":[19],"on":[20],"intermediate":[21],"geometric":[22],"features":[23,84],"or":[24,104],"handcrafted":[25,105],"descriptors,":[26],"limiting":[27],"their":[28],"effectiveness":[29],"under":[30],"non-isometric":[31],"deformations,":[32],"partial":[33],"data,":[34],"non-manifold":[36],"inputs.":[37],"To":[38],"overcome":[39],"these":[40],"issues,":[41],"we":[42],"introduce":[43],"RINO,":[44],"an":[45],"unsupervised,":[46],"rotation-invariant":[47],"dense":[48],"framework":[50],"that":[51,71,97],"effectively":[52],"unifies":[53],"rigid":[54],"non-rigid":[56,116],"matching.":[58],"The":[59],"core":[60],"of":[61,112],"our":[62],"method":[63],"is":[64],"the":[65,99],"novel":[66],"RINONet,":[67],"feature":[69],"extractor":[70],"integrates":[72],"vector-based":[73],"SO(3)-invariant":[74],"with":[76],"orientation-aware":[77],"complex":[78],"functional":[79],"maps":[80],"to":[81],"extract":[82],"robust":[83],"directly":[85],"from":[86],"raw":[87],"geometry.":[88],"This":[89],"allows":[90],"for":[91,101],"fully":[93],"end-to-end,":[94],"data-driven":[95],"approach":[96],"bypasses":[98],"need":[100],"pre-alignment":[103],"features.":[106],"Extensive":[107],"experiments":[108],"show":[109],"unprecedented":[110],"performance":[111],"RINO":[113],"across":[114],"challenging":[115],"matching":[117],"tasks,":[118],"including":[119],"arbitrary":[120],"poses,":[121],"non-isometry,":[122],"partiality,":[123],"non-manifoldness,":[124],"noise.":[126]},"counts_by_year":[],"updated_date":"2026-04-02T13:53:19.096889","created_date":"2026-04-02T00:00:00"}
