{"id":"https://openalex.org/W7154240720","doi":"https://doi.org/10.48550/arxiv.2604.09639","title":"3D Multi-View Stylization with Pose-Free Correspondences Matching for Robust 3D Geometry Preservation","display_name":"3D Multi-View Stylization with Pose-Free Correspondences Matching for Robust 3D Geometry Preservation","publication_year":2026,"publication_date":"2026-03-22","ids":{"openalex":"https://openalex.org/W7154240720","doi":"https://doi.org/10.48550/arxiv.2604.09639"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.09639","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09639","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","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.2604.09639","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5133586614","display_name":"Shirsha Bose","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Bose, Shirsha","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":["https://openalex.org/A5133586614"],"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.4993000030517578,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.4993000030517578,"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/T10719","display_name":"3D Shape Modeling and Analysis","score":0.3237000107765198,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.05139999836683273,"subfield":{"id":"https://openalex.org/subfields/1704","display_name":"Computer Graphics and Computer-Aided Design"},"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/consistency","display_name":"Consistency (knowledge bases)","score":0.4449000060558319},{"id":"https://openalex.org/keywords/matching","display_name":"Matching (statistics)","score":0.41260001063346863},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.40220001339912415},{"id":"https://openalex.org/keywords/epipolar-geometry","display_name":"Epipolar geometry","score":0.4002000093460083},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.3783000111579895},{"id":"https://openalex.org/keywords/view-synthesis","display_name":"View synthesis","score":0.36579999327659607},{"id":"https://openalex.org/keywords/ground-truth","display_name":"Ground truth","score":0.35120001435279846},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3488999903202057}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.713699996471405},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6328999996185303},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5199000239372253},{"id":"https://openalex.org/C2776436953","wikidata":"https://www.wikidata.org/wiki/Q5163215","display_name":"Consistency (knowledge bases)","level":2,"score":0.4449000060558319},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.41260001063346863},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.40220001339912415},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.4002000093460083},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.3804999887943268},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3783000111579895},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.36579999327659607},{"id":"https://openalex.org/C146849305","wikidata":"https://www.wikidata.org/wiki/Q370766","display_name":"Ground truth","level":2,"score":0.35120001435279846},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C53533937","wikidata":"https://www.wikidata.org/wiki/Q185020","display_name":"Histogram","level":3,"score":0.33660000562667847},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.32749998569488525},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.2955000102519989},{"id":"https://openalex.org/C92757383","wikidata":"https://www.wikidata.org/wiki/Q382497","display_name":"Affine transformation","level":2,"score":0.29019999504089355},{"id":"https://openalex.org/C126780896","wikidata":"https://www.wikidata.org/wiki/Q899871","display_name":"Distortion (music)","level":4,"score":0.2827000021934509},{"id":"https://openalex.org/C158843486","wikidata":"https://www.wikidata.org/wiki/Q2137810","display_name":"Complex geometry","level":2,"score":0.28029999136924744},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.27790001034736633},{"id":"https://openalex.org/C3004257","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Correspondence problem","level":2,"score":0.26980000734329224},{"id":"https://openalex.org/C74050887","wikidata":"https://www.wikidata.org/wiki/Q848368","display_name":"Rotation (mathematics)","level":2,"score":0.2624000012874603},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.2612999975681305}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.09639","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09639","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.09639","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.09639","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":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/11","score":0.6872803568840027,"display_name":"Sustainable cities and communities"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Artistic":[0],"style":[1,108],"transfer":[2,87],"is":[3,92],"well":[4],"studied":[5],"for":[6,55],"images":[7],"and":[8,37,44,123,151,167,174,176,181,186,196,208,219,225,229,242],"videos,":[9],"but":[10],"extending":[11],"it":[12],"to":[13,106,132,156],"multi-view":[14,45,50,141],"3D":[15,57,66,201],"scenes":[16,233],"remains":[17,53],"difficult":[18],"because":[19],"stylization":[20,30,51,74],"can":[21],"disrupt":[22],"correspondences":[23],"needed":[24],"by":[25,94,191],"geometry-aware":[26],"pipelines.":[27],"Independent":[28],"per-view":[29],"often":[31],"causes":[32],"texture":[33],"drift,":[34],"warped":[35],"edges,":[36],"inconsistent":[38],"shading,":[39],"degrading":[40],"SLAM,":[41],"depth":[42,168,220],"prediction,":[43],"reconstruction.":[46],"This":[47],"thesis":[48],"addresses":[49],"that":[52],"usable":[54],"downstream":[56],"tasks":[58],"without":[59],"assuming":[60],"camera":[61],"poses":[62],"or":[63],"an":[64,95],"explicit":[65],"representation":[67],"during":[68],"training.":[69],"We":[70,143,170],"introduce":[71],"a":[72,82,99,107,117,128,146],"feed-forward":[73],"network":[75],"trained":[76],"with":[77,88,135,234],"per-scene":[78],"test-time":[79],"optimization":[80],"under":[81],"composite":[83],"objective":[84],"coupling":[85],"appearance":[86],"geometry":[89,166],"preservation.":[90],"Stylization":[91],"driven":[93],"AdaIN-inspired":[96],"loss":[97,120,148],"from":[98,127,138],"frozen":[100],"VGG-19":[101],"encoder,":[102],"matching":[103],"channel-wise":[104],"moments":[105],"image.":[109],"To":[110],"stabilize":[111],"structure":[112,187],"across":[113],"viewpoints,":[114],"we":[115,203],"propose":[116],"correspondence-based":[118],"consistency":[119,244],"using":[121,149,179],"SuperPoint":[122],"SuperGlue,":[124],"constraining":[125],"descriptors":[126,137],"stylized":[129],"anchor":[130],"view":[131],"remain":[133],"consistent":[134],"matched":[136],"the":[139],"original":[140],"set.":[142],"also":[144],"impose":[145],"depth-preservation":[147],"MiDaS/DPT":[150],"use":[152,204],"global":[153],"color":[154],"alignment":[155],"reduce":[157,222],"depth-model":[158],"domain":[159],"shift.":[160],"A":[161],"staged":[162],"weight":[163],"schedule":[164],"introduces":[165],"constraints.":[169],"evaluate":[171],"on":[172,212,232],"Tanks":[173],"Temples":[175],"Mip-NeRF":[177],"360":[178],"image":[180],"reconstruction":[182],"metrics.":[183],"Style":[184],"adherence":[185],"retention":[188],"are":[189],"measured":[190],"Color":[192],"Histogram":[193],"Distance":[194,198],"(CHD)":[195],"Structure":[197],"(DSD).":[199],"For":[200],"consistency,":[202],"monocular":[205],"DROID-SLAM":[206],"trajectories":[207],"symmetric":[209],"Chamfer":[210],"distance":[211],"back-projected":[213],"point":[214],"clouds.":[215],"Across":[216],"ablations,":[217],"correspondence":[218],"regularization":[221],"structural":[223],"distortion":[224],"improve":[226],"SLAM":[227],"stability":[228],"reconstructed":[230],"geometry;":[231],"MuVieCAST":[235],"baselines,":[236],"our":[237],"method":[238],"yields":[239],"stronger":[240],"trajectory":[241],"point-cloud":[243],"while":[245],"maintaining":[246],"competitive":[247],"stylization.":[248]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-04-15T00:00:00"}
