{"id":"https://openalex.org/W7139942147","doi":"https://doi.org/10.48550/arxiv.2603.19193","title":"Reconstruction Matters: Learning Geometry-Aligned BEV Representation through 3D Gaussian Splatting","display_name":"Reconstruction Matters: Learning Geometry-Aligned BEV Representation through 3D Gaussian Splatting","publication_year":2026,"publication_date":"2026-03-19","ids":{"openalex":"https://openalex.org/W7139942147","doi":"https://doi.org/10.48550/arxiv.2603.19193"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.19193","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19193","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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.19193","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5130231773","display_name":"Yiren Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lu, Yiren","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130245868","display_name":"Xin Ye","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Xin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5031984988","display_name":"Burhaneddin Yaman","orcid":"https://orcid.org/0000-0003-0791-5900"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yaman, Burhaneddin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5044813918","display_name":"Jingru Luo","orcid":"https://orcid.org/0000-0002-2518-151X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Luo, Jingru","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023889917","display_name":"Zhexiao Xiong","orcid":"https://orcid.org/0000-0001-5233-1520"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xiong, Zhexiao","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5130250010","display_name":"Liu Ren","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Liu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5130232345","display_name":"Yu Yin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yin, Yu","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/T10531","display_name":"Advanced Vision and Imaging","score":0.35199999809265137,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.35199999809265137,"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/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.22429999709129333,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.1023000031709671,"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/representation","display_name":"Representation (politics)","score":0.6902999877929688},{"id":"https://openalex.org/keywords/generator","display_name":"Generator (circuit theory)","score":0.6132000088691711},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.47620001435279846},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.4691999852657318},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.46309998631477356},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.46149998903274536},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.3955000042915344},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.37369999289512634}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7222999930381775},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6902999877929688},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6861000061035156},{"id":"https://openalex.org/C2780992000","wikidata":"https://www.wikidata.org/wiki/Q17016113","display_name":"Generator (circuit theory)","level":3,"score":0.6132000088691711},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.572700023651123},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.47620001435279846},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.4691999852657318},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.46309998631477356},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.46149998903274536},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3955000042915344},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.37369999289512634},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3564000129699707},{"id":"https://openalex.org/C61326573","wikidata":"https://www.wikidata.org/wiki/Q1496376","display_name":"Gaussian process","level":3,"score":0.3555000126361847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3553999960422516},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.3540000021457672},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.34459999203681946},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.3273000121116638},{"id":"https://openalex.org/C109950114","wikidata":"https://www.wikidata.org/wiki/Q4464732","display_name":"3D reconstruction","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C2779038628","wikidata":"https://www.wikidata.org/wiki/Q7248497","display_name":"Programming by demonstration","level":3,"score":0.2879999876022339},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.28700000047683716},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2786000072956085},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2777000069618225},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.19193","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19193","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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.19193","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.19193","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":"Preprint"},"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":{"Bird's-Eye-View":[0],"(BEV)":[1],"perception":[2,40,69],"serves":[3],"as":[4,27,71,160],"a":[5,11,72,106,131],"cornerstone":[6],"for":[7,22,98,110,162],"autonomous":[8],"driving,":[9],"offering":[10],"unified":[12],"spatial":[13],"representation":[14,96],"that":[15,92,120,134,173],"fuses":[16],"surrounding-view":[17],"images":[18],"to":[19,84,115,158],"enable":[20],"reasoning":[21],"various":[23],"downstream":[24,61,163],"tasks,":[25],"such":[26],"semantic":[28],"segmentation,":[29],"3D":[30,78,95,137,185],"object":[31],"detection,":[32],"and":[33,57,81,102,125,169,178],"motion":[34],"prediction.":[35],"However,":[36],"most":[37],"existing":[38],"BEV":[39,55,100,111,117,156,188],"frameworks":[41],"adopt":[42],"an":[43,93],"end-to-end":[44],"training":[45],"paradigm,":[46],"where":[47],"image":[48],"features":[49],"are":[50,121,151],"directly":[51],"transformed":[52],"into":[53,154,187],"the":[54,67,143,155,180],"space":[56,157],"optimized":[58],"solely":[59],"through":[60],"task":[62],"supervision.":[63],"This":[64],"formulation":[65],"treats":[66],"entire":[68],"process":[70],"black":[73],"box,":[74],"often":[75],"lacking":[76],"explicit":[77,94,184],"geometric":[79],"understanding":[80],"interpretability,":[82],"leading":[83],"suboptimal":[85],"performance.":[86],"In":[87],"this":[88],"paper,":[89],"we":[90,103],"claim":[91],"matters":[97],"accurate":[99],"perception,":[101],"propose":[104],"Splat2BEV,":[105],"Gaussian":[107,132],"Splatting-assisted":[108],"framework":[109],"tasks.":[112,164],"Splat2BEV":[113,174],"aims":[114],"learn":[116],"feature":[118,147],"representations":[119,150],"both":[122],"semantically":[123],"rich":[124],"geometrically":[126],"precise.":[127],"We":[128],"first":[129],"pre-train":[130],"generator":[133],"explicitly":[135],"reconstructs":[136],"scenes":[138],"from":[139],"multi-view":[140],"inputs,":[141],"enabling":[142],"generation":[144],"of":[145,182],"geometry-aligned":[146],"representations.":[148],"These":[149],"then":[152],"projected":[153],"serve":[159],"inputs":[161],"Extensive":[165],"experiments":[166],"on":[167],"nuScenes":[168],"argoverse":[170],"dataset":[171],"demonstrate":[172],"achieves":[175],"state-of-the-art":[176],"performance":[177],"validate":[179],"effectiveness":[181],"incorporating":[183],"reconstruction":[186],"perception.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-03-21T00:00:00"}
