{"id":"https://openalex.org/W7138086294","doi":"https://doi.org/10.1609/aaai.v40i12.37981","title":"Towards 3D Object-Centric Feature Learning for Semantic Scene Completion","display_name":"Towards 3D Object-Centric Feature Learning for Semantic Scene Completion","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138086294","doi":"https://doi.org/10.1609/aaai.v40i12.37981"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i12.37981","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i12.37981","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i12.37981","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129642043","display_name":"Weihua Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Weihua Wang","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China\nNational Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, Liaoning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China\nNational Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5066263434","display_name":"Yubo Cui","orcid":"https://orcid.org/0000-0001-5302-0484"},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yubo Cui","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5041412266","display_name":"Xiangru Lin","orcid":"https://orcid.org/0009-0008-3089-6414"},"institutions":[{"id":"https://openalex.org/I889458895","display_name":"University of Hong Kong","ror":"https://ror.org/02zhqgq86","country_code":"HK","type":"education","lineage":["https://openalex.org/I889458895"]}],"countries":["HK"],"is_corresponding":false,"raw_author_name":"Xiangru Lin","raw_affiliation_strings":["The University of Hong Kong"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"The University of Hong Kong","institution_ids":["https://openalex.org/I889458895"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129735066","display_name":"Zhiheng Li","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhiheng Li","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China","institution_ids":["https://openalex.org/I9224756"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5129746672","display_name":"Zheng Fang","orcid":null},"institutions":[{"id":"https://openalex.org/I9224756","display_name":"Northeastern University","ror":"https://ror.org/03awzbc87","country_code":"CN","type":"education","lineage":["https://openalex.org/I9224756"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zheng Fang","raw_affiliation_strings":["Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China\nNational Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, Liaoning, China\nThe Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University), China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Faculty of Robot Science and Engineering, Northeastern University, Shenyang, Liaoning, China\nNational Frontiers Science Center for Industrial Intelligence and Systems Optimization, Shenyang, Liaoning, China\nThe Key Laboratory of Data Analytics and Optimization for Smart Industry(Northeastern University), China","institution_ids":["https://openalex.org/I9224756"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":5,"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":0.25698324,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"12","first_page":"10136","last_page":"10144"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.6852999925613403,"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"}},"topics":[{"id":"https://openalex.org/T10719","display_name":"3D Shape Modeling and Analysis","score":0.6852999925613403,"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/T10775","display_name":"Generative Adversarial Networks and Image Synthesis","score":0.06710000336170197,"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":0.05490000173449516,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/segmentation","display_name":"Segmentation","score":0.6639999747276306},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.5722000002861023},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5648999810218811},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5583000183105469},{"id":"https://openalex.org/keywords/aggregate","display_name":"Aggregate (composite)","score":0.5328999757766724},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.49380001425743103},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.48399999737739563},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.45660001039505005},{"id":"https://openalex.org/keywords/feature-learning","display_name":"Feature learning","score":0.41679999232292175}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7968999743461609},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7117999792098999},{"id":"https://openalex.org/C89600930","wikidata":"https://www.wikidata.org/wiki/Q1423946","display_name":"Segmentation","level":2,"score":0.6639999747276306},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.5722000002861023},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5648999810218811},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5583000183105469},{"id":"https://openalex.org/C4679612","wikidata":"https://www.wikidata.org/wiki/Q866298","display_name":"Aggregate (composite)","level":2,"score":0.5328999757766724},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.49380001425743103},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.48399999737739563},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.42100000381469727},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.41679999232292175},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.3741999864578247},{"id":"https://openalex.org/C124504099","wikidata":"https://www.wikidata.org/wiki/Q56933","display_name":"Image segmentation","level":3,"score":0.3601999878883362},{"id":"https://openalex.org/C2775955345","wikidata":"https://www.wikidata.org/wiki/Q7449071","display_name":"Semantic mapping","level":2,"score":0.3440000116825104},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.33970001339912415},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.33469998836517334},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.31869998574256897},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.30979999899864197},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.2996000051498413},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.2921000123023987},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.28279998898506165},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.2685999870300293},{"id":"https://openalex.org/C22367795","wikidata":"https://www.wikidata.org/wiki/Q7625208","display_name":"Structured prediction","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i12.37981","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i12.37981","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:ojs.aaai.org:article/37981","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37981","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"2159-5399","raw_type":"info:eu-repo/semantics/publishedVersion"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i12.37981","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i12.37981","pdf_url":null,"source":{"id":"https://openalex.org/S4210191458","display_name":"Proceedings of the AAAI Conference on Artificial Intelligence","issn_l":"2159-5399","issn":["2159-5399","2374-3468"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/P4310320058","host_organization_name":"Association for the Advancement of Artificial Intelligence","host_organization_lineage":["https://openalex.org/P4310320058"],"host_organization_lineage_names":["Association for the Advancement of Artificial Intelligence"],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the AAAI Conference on Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[{"score":0.8141981959342957,"id":"https://metadata.un.org/sdg/14","display_name":"Life below water"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Vision-based":[0],"3D":[1,97,111],"Semantic":[2,98],"Scene":[3],"Completion":[4],"(SSC)":[5],"has":[6],"received":[7],"growing":[8],"attention":[9,105],"due":[10],"to":[11,41,69,85,106],"its":[12],"potential":[13],"in":[14,47,110,157],"autonomous":[15],"driving.":[16],"While":[17],"most":[18],"existing":[19],"approaches":[20],"follow":[21],"an":[22,57,138],"ego-centric":[23],"paradigm":[24],"by":[25],"aggregating":[26],"and":[27,43,117,151,166,180],"diffusing":[28],"features":[29,109,131,146],"over":[30],"the":[31,63,90,154,158,164],"entire":[32],"scene,":[33],"they":[34],"often":[35],"overlook":[36],"fine-grained":[37],"object-level":[38],"details,":[39],"leading":[40],"semantic":[42,73],"geometric":[44],"ambiguities,":[45],"especially":[46],"complex":[48],"environments.":[49],"To":[50,113],"address":[51],"this":[52],"limitation,":[53],"we":[54,77,94,120,136],"propose":[55,137],"Ocean,":[56],"object-centric":[58,108],"prediction":[59],"framework":[60],"that":[61,102,128,143,170],"decomposes":[62],"scene":[64,155],"into":[65],"individual":[66],"object":[67],"instances":[68],"enable":[70],"more":[71],"accurate":[72],"occupancy":[74],"prediction.":[75],"Specifically,":[76],"first":[78],"employ":[79],"a":[80,96,123,148],"lightweight":[81],"segmentation":[82,115,130],"model,":[83],"MobileSAM,":[84],"extract":[86],"instance":[87,145],"masks":[88],"from":[89],"input":[91],"image.":[92],"Then,":[93],"introduce":[95],"Group":[99],"Attention":[100,126],"module":[101,127,142],"leverages":[103,129],"linear":[104],"aggregate":[107],"space.":[112,160],"handle":[114],"errors":[116],"missing":[118],"instances,":[119],"further":[121],"design":[122],"Global":[124],"Similarity-Guided":[125],"for":[132],"global":[133],"interaction.":[134],"Finally,":[135],"Instance-aware":[139],"Local":[140],"Diffusion":[141],"improves":[144],"through":[147],"generative":[149],"process":[150],"subsequently":[152],"refines":[153],"representation":[156],"BEV":[159],"Extensive":[161],"experiments":[162],"on":[163],"SemanticKITTI":[165],"SSCBench-KITTI360":[167],"benchmarks":[168],"demonstrate":[169],"Ocean":[171],"achieves":[172],"state-of-the-art":[173],"performance,":[174],"with":[175],"mIoU":[176],"scores":[177],"of":[178],"17.40":[179],"20.28,":[181],"respectively.":[182]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-03-18T00:00:00"}