{"id":"https://openalex.org/W4403664032","doi":"https://doi.org/10.1109/iccv51701.2025.02691","title":"GaussianOcc: Fully Self-Supervised and Efficient 3D Occupancy Estimation with Gaussian Splatting","display_name":"GaussianOcc: Fully Self-Supervised and Efficient 3D Occupancy Estimation with Gaussian Splatting","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4403664032","doi":"https://doi.org/10.1109/iccv51701.2025.02691"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.02691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2408.11447","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5013378205","display_name":"Wanshui Gan","orcid":"https://orcid.org/0000-0002-6720-6500"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Wanshui Gan","raw_affiliation_strings":["The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100609965","display_name":"Fang Liu","orcid":"https://orcid.org/0000-0002-6213-9572"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Fang Liu","raw_affiliation_strings":["The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5016248876","display_name":"Hongbin Xu","orcid":"https://orcid.org/0000-0002-3455-1527"},"institutions":[{"id":"https://openalex.org/I90610280","display_name":"South China University of Technology","ror":"https://ror.org/0530pts50","country_code":"CN","type":"education","lineage":["https://openalex.org/I90610280"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hongbin Xu","raw_affiliation_strings":["South China University of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"South China University of Technology","institution_ids":["https://openalex.org/I90610280"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041189494","display_name":"Ningkai Mo","orcid":null},"institutions":[{"id":"https://openalex.org/I19820366","display_name":"Chinese Academy of Sciences","ror":"https://ror.org/034t30j35","country_code":"CN","type":"government","lineage":["https://openalex.org/I19820366"]},{"id":"https://openalex.org/I4210145761","display_name":"Shenzhen Institutes of Advanced Technology","ror":"https://ror.org/04gh4er46","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Ningkai Mo","raw_affiliation_strings":["Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences","institution_ids":["https://openalex.org/I19820366","https://openalex.org/I4210145761"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5034435383","display_name":"Naoto Yokoya","orcid":"https://orcid.org/0000-0002-7321-4590"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Naoto Yokoya","raw_affiliation_strings":["The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"28980","last_page":"28990"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9962000250816345,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.9962000250816345,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9739000201225281,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12740","display_name":"Gait Recognition and Analysis","score":0.9563000202178955,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"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/occupancy","display_name":"Occupancy","score":0.8377365469932556},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6710984706878662},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6497277021408081},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.6043654084205627},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4507449269294739},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.06663548946380615},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.06522312760353088}],"concepts":[{"id":"https://openalex.org/C160331591","wikidata":"https://www.wikidata.org/wiki/Q7075743","display_name":"Occupancy","level":2,"score":0.8377365469932556},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6710984706878662},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6497277021408081},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.6043654084205627},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4507449269294739},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.06663548946380615},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.06522312760353088},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C170154142","wikidata":"https://www.wikidata.org/wiki/Q150737","display_name":"Architectural engineering","level":1,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.02691","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.02691","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2408.11447","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.11447","pdf_url":"https://arxiv.org/pdf/2408.11447","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2408.11447","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2408.11447","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":"pmh:oai:arXiv.org:2408.11447","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2408.11447","pdf_url":"https://arxiv.org/pdf/2408.11447","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G452636178","display_name":null,"funder_award_id":"JPMJFR206S","funder_id":"https://openalex.org/F4320320907","funder_display_name":"Japan Science and Technology Corporation"},{"id":"https://openalex.org/G5535165727","display_name":null,"funder_award_id":"JPMJFR206S","funder_id":"https://openalex.org/F4320338248","funder_display_name":"Fusion Oriented REsearch for disruptive Science and Technology"},{"id":"https://openalex.org/G6383204423","display_name":null,"funder_award_id":"22H03609","funder_id":"https://openalex.org/F4320334764","funder_display_name":"Japan Society for the Promotion of Science"}],"funders":[{"id":"https://openalex.org/F4320320907","display_name":"Japan Science and Technology Corporation","ror":"https://ror.org/00097mb19"},{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"},{"id":"https://openalex.org/F4320338248","display_name":"Fusion Oriented REsearch for disruptive Science and Technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W4282043467","https://openalex.org/W2105697914","https://openalex.org/W3093197249","https://openalex.org/W1968324288","https://openalex.org/W1540010871","https://openalex.org/W3023979140","https://openalex.org/W3177545769"],"abstract_inverted_index":{"We":[0,95],"introduce":[1],"GaussianOcc,":[2],"a":[3,113],"systematic":[4],"method":[5,118],"that":[6],"investigates":[7],"the":[8,105,115],"two":[9],"usages":[10],"of":[11,109],"Gaussian":[12,49,97,110],"splatting":[13],"for":[14,28,51,60,75],"fully":[15,61,120],"self-supervised":[16,29,62,121],"and":[17,92,141],"efficient":[18],"3D":[19,30,77,126],"occupancy":[20,31,127],"estimation":[21,32,128],"in":[22,129,139,145,152],"surround":[23],"views.":[24],"First,":[25],"traditional":[26],"methods":[27,70],"still":[33],"require":[34],"ground":[35,123],"truth":[36,124],"6D":[37],"poses":[38],"from":[39,64,99],"sensors":[40],"during":[41],"training.":[42],"To":[43],"address":[44],"this":[45],"limitation,":[46],"we":[47],"propose":[48,96],"Splatting":[50,98],"Projection":[52],"(GSP)":[53],"module":[54],"to":[55,103],"provide":[56],"accurate":[57],"scale":[58],"information":[59],"training":[63,140],"adjacent":[65],"view":[66],"projection.":[67],"Additionally,":[68],"existing":[69],"rely":[71],"on":[72],"volume":[73],"rendering":[74,107],"final":[76],"voxel":[78],"representation":[79],"learning":[80],"using":[81],"2D":[82],"signals":[83],"(depth":[84],"maps,":[85],"semantic":[86],"maps),":[87],"which":[88],"is":[89,150],"both":[90],"time-consuming":[91],"less":[93],"effective.":[94],"Voxel":[100],"space":[101],"(GSV)":[102],"leverage":[104],"fast":[106],"properties":[108],"splatting.":[111],"As":[112],"result,":[114],"proposed":[116],"GaussianOcc":[117],"enables":[119],"(no":[122],"pose)":[125],"competitive":[130],"performance":[131],"with":[132],"low":[133],"computational":[134],"cost":[135],"(2.7":[136],"times":[137,143],"faster":[138,144],"5":[142],"rendering).":[146],"The":[147],"relevant":[148],"code":[149],"available":[151],"https://github.com/GANWANSHUI/GaussianOcc.git.":[153]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-10-10T00:00:00"}
