{"id":"https://openalex.org/W7225650834","doi":"https://doi.org/10.1145/3842581","title":"MeRM: Large Mesh Reconstruction Model via Neural Geometry Tokens","display_name":"MeRM: Large Mesh Reconstruction Model via Neural Geometry Tokens","publication_year":2026,"publication_date":"2026-11-09","ids":{"openalex":"https://openalex.org/W7225650834","doi":"https://doi.org/10.1145/3842581"},"language":"en","primary_location":{"id":"doi:10.1145/3842581","doi":"https://doi.org/10.1145/3842581","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3842581","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-a","cwts-core","dongbi-a","jufo-3","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.1145/3842581","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100420888","display_name":"Kai Ye","orcid":"https://orcid.org/0000-0003-4696-3948","observed_orcids":["https://orcid.org/0000-0003-4696-3948","https://orcid.org/0009-0004-1500-0000","https://orcid.org/0009-0006-9691-1125"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Ye","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-9691-1125","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5161331037","display_name":"Haoru Wang","orcid":"https://orcid.org/0009-0006-6968-7287","observed_orcids":["https://orcid.org/0009-0006-6968-7287"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoru Wang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0006-6968-7287","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5151890618","display_name":"Zhongyu Shi","orcid":"https://orcid.org/0009-0004-1008-1809","observed_orcids":["https://orcid.org/0009-0004-1008-1809"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhongyu Shi","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0004-1008-1809","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100751872","display_name":"Ding Liang","orcid":"https://orcid.org/0000-0001-9774-4687","observed_orcids":["https://orcid.org/0000-0001-9774-4687"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding Liang","raw_affiliation_strings":["VAST AI, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-9774-4687","affiliations":[{"raw_affiliation_string":"VAST AI, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091525681","display_name":"Yan\u2010Pei Cao","orcid":"https://orcid.org/0000-0002-0416-4374","observed_orcids":["https://orcid.org/0000-0002-0416-4374"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yan-Pei Cao","raw_affiliation_strings":["VAST AI, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-0416-4374","affiliations":[{"raw_affiliation_string":"VAST AI, Beijing, China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010254581","display_name":"Wenzheng Chen","orcid":"https://orcid.org/0009-0008-5623-1963","observed_orcids":["https://orcid.org/0009-0008-5623-1963"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenzheng Chen","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0009-0008-5623-1963","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5010714340","display_name":"Baoquan Chen","orcid":"https://orcid.org/0000-0003-4702-036X","observed_orcids":["https://orcid.org/0000-0003-4702-036X"]},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Baoquan Chen","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4702-036X","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"45","issue":"6","first_page":"1","last_page":"16"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9965999722480774,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.9965999722480774,"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"}},{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.002300000051036477,"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/T10481","display_name":"Computer Graphics and Visualization Techniques","score":0.0006000000284984708,"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/mesh-reconstruction","display_name":"mesh reconstruction","score":0.8489999771118164},{"id":"https://openalex.org/keywords/feed-forward-3d-reconstruction","display_name":"feed-forward 3D reconstruction","score":0.746999979019165},{"id":"https://openalex.org/keywords/geometric-ambiguity","display_name":"geometric ambiguity","score":0.5350000262260437},{"id":"https://openalex.org/keywords/large-scale-3d-models","display_name":"large-scale 3D models","score":0.5210000276565552}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6930999755859375},{"id":"https://openalex.org/C20885615","wikidata":"https://www.wikidata.org/wiki/Q825595","display_name":"Surface reconstruction","level":3,"score":0.6553999781608582},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6474999785423279},{"id":"https://openalex.org/C131979681","wikidata":"https://www.wikidata.org/wiki/Q1899648","display_name":"Point cloud","level":2,"score":0.6340000033378601},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5662000179290771},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.5102999806404114},{"id":"https://openalex.org/C2776799497","wikidata":"https://www.wikidata.org/wiki/Q484298","display_name":"Surface (topology)","level":2,"score":0.503000020980835},{"id":"https://openalex.org/C23379248","wikidata":"https://www.wikidata.org/wiki/Q200904","display_name":"Epipolar geometry","level":3,"score":0.49939998984336853},{"id":"https://openalex.org/C31487907","wikidata":"https://www.wikidata.org/wiki/Q1154597","display_name":"Polygon mesh","level":2,"score":0.3896999955177307},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.3865000009536743},{"id":"https://openalex.org/C108010975","wikidata":"https://www.wikidata.org/wiki/Q500094","display_name":"Pruning","level":2,"score":0.3804999887943268},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.3799999952316284},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3693999946117401},{"id":"https://openalex.org/C181095308","wikidata":"https://www.wikidata.org/wiki/Q1541599","display_name":"Geometric primitive","level":2,"score":0.3578000068664551},{"id":"https://openalex.org/C2777735758","wikidata":"https://www.wikidata.org/wiki/Q817765","display_name":"Path (computing)","level":2,"score":0.34470000863075256},{"id":"https://openalex.org/C44365914","wikidata":"https://www.wikidata.org/wiki/Q17120636","display_name":"Photometric stereo","level":3,"score":0.34139999747276306},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.3375000059604645},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.33629998564720154},{"id":"https://openalex.org/C135981907","wikidata":"https://www.wikidata.org/wiki/Q188056","display_name":"Triangulation","level":2,"score":0.3276999890804291},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3172000050544739},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.31220000982284546},{"id":"https://openalex.org/C102634674","wikidata":"https://www.wikidata.org/wiki/Q868473","display_name":"Smoothness","level":2,"score":0.31049999594688416},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.30730000138282776},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.30480000376701355},{"id":"https://openalex.org/C29123130","wikidata":"https://www.wikidata.org/wiki/Q874709","display_name":"Computational geometry","level":2,"score":0.30079999566078186},{"id":"https://openalex.org/C62354387","wikidata":"https://www.wikidata.org/wiki/Q875399","display_name":"Boundary (topology)","level":2,"score":0.2922999858856201},{"id":"https://openalex.org/C206423108","wikidata":"https://www.wikidata.org/wiki/Q214728","display_name":"B\u00e9zier curve","level":2,"score":0.29159998893737793},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29109999537467957},{"id":"https://openalex.org/C65909025","wikidata":"https://www.wikidata.org/wiki/Q1945033","display_name":"Monocular","level":2,"score":0.2906000018119812},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2750999927520752},{"id":"https://openalex.org/C137800194","wikidata":"https://www.wikidata.org/wiki/Q11713455","display_name":"Interpolation (computer graphics)","level":3,"score":0.2669000029563904},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.2653000056743622},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.2630000114440918},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.26269999146461487},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.26249998807907104},{"id":"https://openalex.org/C205711294","wikidata":"https://www.wikidata.org/wiki/Q176953","display_name":"Rendering (computer graphics)","level":2,"score":0.2547999918460846},{"id":"https://openalex.org/C104065381","wikidata":"https://www.wikidata.org/wiki/Q1002535","display_name":"Geometric modeling","level":2,"score":0.2538999915122986},{"id":"https://openalex.org/C2779898584","wikidata":"https://www.wikidata.org/wiki/Q7820109","display_name":"Reconstruction algorithm","level":3,"score":0.25290000438690186}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3842581","doi":"https://doi.org/10.1145/3842581","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3842581","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-a","cwts-core","dongbi-a","jufo-3","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.1145/3842581","doi":"https://doi.org/10.1145/3842581","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3842581","pdf_url":null,"source":{"id":"https://openalex.org/S185367456","display_name":"ACM Transactions on Graphics","issn_l":"0730-0301","issn":["0730-0301","1557-7368"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["anvur-scientific","ccf-a","cwts-core","dongbi-a","jufo-3","norway-2","poland-140","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Graphics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"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":48,"referenced_works":["https://openalex.org/W2147180865","https://openalex.org/W2178629455","https://openalex.org/W2249773824","https://openalex.org/W2257063750","https://openalex.org/W2331128040","https://openalex.org/W3173522942","https://openalex.org/W3190965961","https://openalex.org/W4285102264","https://openalex.org/W4303647933","https://openalex.org/W4323927218","https://openalex.org/W4376122412","https://openalex.org/W4385275410","https://openalex.org/W4385275714","https://openalex.org/W4386066812","https://openalex.org/W4386075660","https://openalex.org/W4386076002","https://openalex.org/W4386076564","https://openalex.org/W4388555505","https://openalex.org/W4393248012","https://openalex.org/W4394972252","https://openalex.org/W4400822286","https://openalex.org/W4402703685","https://openalex.org/W4402715971","https://openalex.org/W4402726963","https://openalex.org/W4402733576","https://openalex.org/W4402816534","https://openalex.org/W4402951569","https://openalex.org/W4404261781","https://openalex.org/W4404524486","https://openalex.org/W4413146238","https://openalex.org/W4413146830","https://openalex.org/W4413146851","https://openalex.org/W4413157519","https://openalex.org/W4413789567","https://openalex.org/W4415063882","https://openalex.org/W4415307807","https://openalex.org/W4415333916","https://openalex.org/W4415795342","https://openalex.org/W4415797345","https://openalex.org/W4416063870","https://openalex.org/W4416542307","https://openalex.org/W7101756695","https://openalex.org/W7102610667","https://openalex.org/W7120080513","https://openalex.org/W7133236972","https://openalex.org/W7133330195","https://openalex.org/W7160123576","https://openalex.org/W7168733232"],"related_works":["https://openalex.org/W4417272007","https://openalex.org/W4415307807","https://openalex.org/W7135170459","https://openalex.org/W7208787652","https://openalex.org/W4313153331","https://openalex.org/W4415797345","https://openalex.org/W4394972252","https://openalex.org/W4391345134","https://openalex.org/W7127389748","https://openalex.org/W4416551851"],"abstract_inverted_index":{"High-fidelity":[0],"surface":[1,49,64,77,159],"reconstruction":[2,50,65,160],"from":[3,41,146],"sparse":[4,42,195],"RGB":[5],"images":[6],"remains":[7],"a":[8,81,95,103,122,136,202,211],"significant":[9],"challenge,":[10],"where":[11],"classical":[12],"optimization-based":[13,187],"approaches":[14,188],"typically":[15],"fail":[16],"to":[17,47,86,110,125,140],"resolve":[18],"geometric":[19,55,138,150],"ambiguity":[20],"under":[21],"insufficient":[22],"epipolar":[23],"constraints.":[24],"While":[25],"recent":[26],"feed-forward":[27,63,97,178,207],"methods":[28,179],"have":[29],"achieved":[30],"remarkable":[31],"progress":[32],"in":[33,53,62],"directly":[34],"regressing":[35],"point":[36],"clouds":[37],"and":[38,75,84,132,166,180],"3D":[39,76],"Gaussians":[40],"inputs,":[43],"extending":[44],"such":[45],"paradigms":[46],"explicit":[48],"often":[51],"results":[52],"suboptimal":[54],"quality.":[56],"We":[57,197],"identify":[58],"the":[59,142,147,183],"primary":[60],"obstacle":[61],"as":[66,135],"an":[67],"inherent":[68],"structural":[69,143],"misalignment":[70],"between":[71],"2D":[72],"visual":[73],"inputs":[74],"targets,":[78],"which":[79],"creates":[80],"learning":[82],"bottleneck":[83],"leads":[85],"degraded":[87],"performance.":[88],"In":[89],"this":[90,112],"work,":[91],"we":[92],"propose":[93],"MeRM,":[94],"large-scale":[96,206],"Mesh":[98],"Reconstruction":[99],"Model":[100],"that":[101,118,172],"leverages":[102],"novel":[104,203],"Neural":[105],"Geometry":[106],"Token":[107],"(NGT)":[108],"technique":[109],"address":[111],"challenge.":[113],"Our":[114],"key":[115],"insight":[116],"is":[117],"intermediate":[119],"tokens":[120],"of":[121,185],"multi-view":[123],"Transformer\u2014pretrained":[124],"predict":[126],"dense":[127,190],"depth":[128],"maps,":[129,131],"normal":[130],"masks\u2014can":[133],"serve":[134],"powerful":[137],"pre-aggregator":[139],"bridge":[141],"bottleneck.":[144],"Benefiting":[145],"highly":[148],"informative":[149],"cues":[151],"distilled":[152],"by":[153],"NGT,":[154],"our":[155,173,199],"MeRM":[156,174],"delivers":[157],"exceptional":[158],"quality":[161],"while":[162],"maintaining":[163],"impressive":[164],"training":[165],"inference":[167],"efficiency.":[168],"Extensive":[169],"experiments":[170],"demonstrate":[171],"significantly":[175],"outperforms":[176],"prior":[177],"even":[181],"exceeds":[182],"performance":[184],"state-of-the-art":[186],"on":[189],"views,":[191],"despite":[192],"using":[193],"only":[194],"inputs.":[196],"believe":[198],"approach":[200],"establishes":[201],"framework":[204],"for":[205,214],"mesh":[208],"reconstruction,":[209],"paving":[210],"new":[212],"path":[213],"future":[215],"research.":[216]},"counts_by_year":[],"updated_date":"2026-11-11T12:16:26.678958","created_date":"2026-11-10T00:00:00"}
