{"id":"https://openalex.org/W4415538229","doi":"https://doi.org/10.1145/3746027.3754964","title":"SLGaussian: Fast Language Gaussian Splatting in Sparse Views","display_name":"SLGaussian: Fast Language Gaussian Splatting in Sparse Views","publication_year":2025,"publication_date":"2025-10-25","ids":{"openalex":"https://openalex.org/W4415538229","doi":"https://doi.org/10.1145/3746027.3754964"},"language":null,"primary_location":{"id":"doi:10.1145/3746027.3754964","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754964","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1145/3746027.3754964","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Kangjie Chen","orcid":"https://orcid.org/0009-0004-1002-015X"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kangjie Chen","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0004-1002-015X","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5083799424","display_name":"Bingquan Dai","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"BingQuan Dai","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0006-8546-5529","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108889598","display_name":"Minghan Qin","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Minghan Qin","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0002-8304-5353","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Dongbin Zhang","orcid":"https://orcid.org/0009-0004-3919-9827"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Dongbin Zhang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0004-3919-9827","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":null,"display_name":"Peihao Li","orcid":"https://orcid.org/0009-0001-2352-8807"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Peihao Li","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0001-2352-8807","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077722799","display_name":"Yingshuang Zou","orcid":null},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yingshuang Zou","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0009-0002-2881-0518","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028229824","display_name":"Haoqian Wang","orcid":"https://orcid.org/0000-0003-2792-8469"},"institutions":[{"id":"https://openalex.org/I4210114105","display_name":"Tsinghua\u2013Berkeley Shenzhen Institute","ror":"https://ror.org/02hhwwz98","country_code":"CN","type":"facility","lineage":["https://openalex.org/I4210114105","https://openalex.org/I95457486","https://openalex.org/I99065089"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haoqian Wang","raw_affiliation_strings":["Tsinghua Shenzhen International Graduate School, Shenzhen, China"],"raw_orcid":"https://orcid.org/0000-0003-2792-8469","affiliations":[{"raw_affiliation_string":"Tsinghua Shenzhen International Graduate School, Shenzhen, China","institution_ids":["https://openalex.org/I4210114105"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I4210114105"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"3047","last_page":"3056"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10036","display_name":"Advanced Neural Network Applications","score":0.9995999932289124,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9987000226974487,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9976999759674072,"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/inference","display_name":"Inference","score":0.6725000143051147},{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.5220999717712402},{"id":"https://openalex.org/keywords/search-engine-indexing","display_name":"Search engine indexing","score":0.5214999914169312},{"id":"https://openalex.org/keywords/viewpoints","display_name":"Viewpoints","score":0.4932999908924103},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.475600004196167},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.46970000863075256},{"id":"https://openalex.org/keywords/sparse-approximation","display_name":"Sparse approximation","score":0.4203000068664551},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.3901999890804291},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.35440000891685486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.820900022983551},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6913999915122986},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.6725000143051147},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5860999822616577},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.5220999717712402},{"id":"https://openalex.org/C75165309","wikidata":"https://www.wikidata.org/wiki/Q2258979","display_name":"Search engine indexing","level":2,"score":0.5214999914169312},{"id":"https://openalex.org/C2776035091","wikidata":"https://www.wikidata.org/wiki/Q7928819","display_name":"Viewpoints","level":2,"score":0.4932999908924103},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.475600004196167},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.46970000863075256},{"id":"https://openalex.org/C124066611","wikidata":"https://www.wikidata.org/wiki/Q28684319","display_name":"Sparse approximation","level":2,"score":0.4203000068664551},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.3901999890804291},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.35440000891685486},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.3521000146865845},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.3474999964237213},{"id":"https://openalex.org/C56372850","wikidata":"https://www.wikidata.org/wiki/Q1050404","display_name":"Sparse matrix","level":3,"score":0.3375999927520752},{"id":"https://openalex.org/C2777472644","wikidata":"https://www.wikidata.org/wiki/Q16968992","display_name":"Approximate inference","level":3,"score":0.3303999900817871},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3303000032901764},{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.30869999527931213},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3012999892234802},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.29269999265670776},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.27639999985694885},{"id":"https://openalex.org/C118505674","wikidata":"https://www.wikidata.org/wiki/Q42586063","display_name":"Encoder","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C2776449333","wikidata":"https://www.wikidata.org/wiki/Q7928781","display_name":"View synthesis","level":3,"score":0.26409998536109924},{"id":"https://openalex.org/C511192102","wikidata":"https://www.wikidata.org/wiki/Q5156948","display_name":"Comprehension","level":2,"score":0.25679999589920044}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3746027.3754964","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754964","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3746027.3754964","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3746027.3754964","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 33rd ACM International Conference on Multimedia","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7636710225","display_name":null,"funder_award_id":"2022YFB36066","funder_id":"https://openalex.org/F4320335777","funder_display_name":"National Key Research and Development Program of China"}],"funders":[{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W2194775991","https://openalex.org/W3176368002","https://openalex.org/W3203570626","https://openalex.org/W4200150166","https://openalex.org/W4312234520","https://openalex.org/W4312912313","https://openalex.org/W4383108296","https://openalex.org/W4383108895","https://openalex.org/W4385318467","https://openalex.org/W4386065742","https://openalex.org/W4386075561","https://openalex.org/W4390872744","https://openalex.org/W4390874575","https://openalex.org/W4402660132","https://openalex.org/W4402713101","https://openalex.org/W4402715971","https://openalex.org/W4402727529","https://openalex.org/W4402727915","https://openalex.org/W4402771875","https://openalex.org/W4413155367"],"related_works":[],"abstract_inverted_index":{"3D":[0,18,56,90,98,110],"semantic":[1,57],"field":[2],"learning":[3],"is":[4,23],"crucial":[5],"for":[6,41,54,80,96],"applications":[7],"like":[8],"autonomous":[9],"navigation,":[10],"AR/VR,":[11],"and":[12,76,113,118,130,142],"robotics,":[13],"where":[14],"accurate":[15,97],"comprehension":[16],"of":[17,65],"scenes":[19],"from":[20,59],"limited":[21],"viewpoints":[22],"essential.":[24],"Existing":[25],"methods":[26,124],"struggle":[27],"under":[28,101,139],"sparse":[29,60,102,109],"view":[30,103],"conditions,":[31],"relying":[32],"on":[33,107],"inefficient":[34],"per-scene":[35],"multi-view":[36],"optimizations,":[37],"which":[38],"are":[39],"impractical":[40],"many":[42],"real-world":[43],"tasks.":[44],"To":[45],"address":[46],"this,":[47],"we":[48],"propose":[49],"SLGaussian,":[50],"a":[51,93],"feed-forward":[52],"method":[53],"constructing":[55],"fields":[58],"viewpoints,":[61],"allowing":[62],"direct":[63],"inference":[64,137],"3DGS-based":[66],"scenes.":[67],"By":[68],"ensuring":[69],"consistent":[70],"SAM":[71],"segmentations":[72],"through":[73],"video":[74],"tracking":[75],"using":[77],"low-dimensional":[78],"indexing":[79],"high-dimensional":[81],"CLIP":[82],"features,":[83],"SLGaussian":[84,121],"efficiently":[85],"embeds":[86],"language":[87],"information":[88],"in":[89,115,125,138,145],"space,":[91],"offering":[92],"robust":[94],"solution":[95],"scene":[99,136],"understanding":[100],"conditions.":[104],"In":[105],"experiments":[106],"two-view":[108],"object":[111],"querying":[112,144],"segmentation":[114],"the":[116],"LERF":[117],"3D-OVS":[119],"datasets,":[120],"outperforms":[122],"existing":[123],"chosen":[126],"IoU,":[127],"Localization":[128],"Accuracy,":[129],"mIoU.":[131],"Moreover,":[132],"our":[133],"model":[134],"achieves":[135],"30":[140],"seconds":[141,148],"open-vocabulary":[143],"just":[146],"0.011":[147],"per":[149],"query.":[150]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-07-17T09:13:05.818461","created_date":"2025-10-25T00:00:00"}