{"id":"https://openalex.org/W7138037566","doi":"https://doi.org/10.1609/aaai.v40i8.37531","title":"Refine3D: Scene-Adaptive Reference Point Refinement for Sparse 3D Object Detection","display_name":"Refine3D: Scene-Adaptive Reference Point Refinement for Sparse 3D Object Detection","publication_year":2026,"publication_date":"2026-03-14","ids":{"openalex":"https://openalex.org/W7138037566","doi":"https://doi.org/10.1609/aaai.v40i8.37531"},"language":"en","primary_location":{"id":"doi:10.1609/aaai.v40i8.37531","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i8.37531","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":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://doi.org/10.1609/aaai.v40i8.37531","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129652492","display_name":"Fan Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fan Li","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129714813","display_name":"Jing Lu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jing Lu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129668670","display_name":"Yunlu Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yunlu Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123015897","display_name":"Changhong Wu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Changhong Wu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129650894","display_name":"Tao Xu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tao Xu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125767871","display_name":"Zhaoyi Xiang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhaoyi Xiang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5129640898","display_name":"Yi Niu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Niu","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":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"40","issue":"8","first_page":"6073","last_page":"6081"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9330000281333923,"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":0.9330000281333923,"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":0.03460000082850456,"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/T11307","display_name":"Domain Adaptation and Few-Shot Learning","score":0.004800000227987766,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/reference-model","display_name":"Reference model","score":0.6502000093460083},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.6265000104904175},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.6158999800682068},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5891000032424927},{"id":"https://openalex.org/keywords/adaptability","display_name":"Adaptability","score":0.5727999806404114},{"id":"https://openalex.org/keywords/reference-data","display_name":"Reference data","score":0.5591999888420105},{"id":"https://openalex.org/keywords/component","display_name":"Component (thermodynamics)","score":0.531499981880188},{"id":"https://openalex.org/keywords/point","display_name":"Point (geometry)","score":0.45719999074935913}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7745000123977661},{"id":"https://openalex.org/C150189527","wikidata":"https://www.wikidata.org/wiki/Q356674","display_name":"Reference model","level":2,"score":0.6502000093460083},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.6265000104904175},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.6158999800682068},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5891000032424927},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5864999890327454},{"id":"https://openalex.org/C177606310","wikidata":"https://www.wikidata.org/wiki/Q5674297","display_name":"Adaptability","level":2,"score":0.5727999806404114},{"id":"https://openalex.org/C60478076","wikidata":"https://www.wikidata.org/wiki/Q3036835","display_name":"Reference data","level":2,"score":0.5591999888420105},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5328999757766724},{"id":"https://openalex.org/C168167062","wikidata":"https://www.wikidata.org/wiki/Q1117970","display_name":"Component (thermodynamics)","level":2,"score":0.531499981880188},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.45719999074935913},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C58489278","wikidata":"https://www.wikidata.org/wiki/Q1172284","display_name":"Data set","level":2,"score":0.3549000024795532},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3472999930381775},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3393000066280365},{"id":"https://openalex.org/C118317068","wikidata":"https://www.wikidata.org/wiki/Q2100760","display_name":"Point distribution model","level":2,"score":0.31470000743865967},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.29510000348091125},{"id":"https://openalex.org/C110121322","wikidata":"https://www.wikidata.org/wiki/Q865811","display_name":"Distribution (mathematics)","level":2,"score":0.28679999709129333},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.2842999994754791},{"id":"https://openalex.org/C151201525","wikidata":"https://www.wikidata.org/wiki/Q177239","display_name":"Limit (mathematics)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2549000084400177}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1609/aaai.v40i8.37531","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i8.37531","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/37531","is_oa":false,"landing_page_url":"https://ojs.aaai.org/index.php/AAAI/article/view/37531","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/article"}],"best_oa_location":{"id":"doi:10.1609/aaai.v40i8.37531","is_oa":true,"landing_page_url":"https://doi.org/10.1609/aaai.v40i8.37531","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":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Sparse":[0],"query-based":[1],"detectors":[2],"have":[3],"emerged":[4],"as":[5,36,76],"the":[6,29,87,104,168],"dominant":[7],"paradigm":[8],"in":[9,43],"camera-only":[10],"3D":[11],"object":[12,73,130],"detection,":[13],"owing":[14],"to":[15,40,123],"their":[16],"exceptional":[17],"performance":[18],"and":[19,92,109,132,174],"computational":[20],"efficiency.":[21],"A":[22],"central":[23],"component":[24],"of":[25,31,55,89,106],"these":[26],"approaches":[27],"is":[28],"use":[30],"reference":[32,56,90,107,125,144],"points,":[33],"which":[34],"serve":[35],"learnable":[37],"spatial":[38],"anchors":[39],"guide":[41],"queries":[42],"localizing":[44],"target":[45],"objects.":[46,111],"However,":[47],"existing":[48],"methods":[49],"typically":[50],"employ":[51],"a":[52,61,116,133],"unified":[53],"set":[54],"points":[57,91,108,126],"across":[58],"all":[59],"scenes,":[60],"design":[62],"we":[63,85,114],"find":[64],"suboptimal":[65],"for":[66,142],"handling":[67],"complex":[68],"scenarios":[69],"with":[70,170],"highly":[71],"imbalanced":[72],"distributions,":[74],"such":[75],"road":[77],"intersections":[78],"or":[79],"occluded":[80],"environments.":[81],"In":[82,112],"this":[83],"paper,":[84],"investigate":[86],"adaptability":[88],"propose":[93],"Refine3D,":[94],"an":[95],"adaptive":[96],"refinement":[97],"mechanism":[98],"that":[99,138,165],"achieves":[100],"scene-level":[101],"alignment":[102],"between":[103],"distribution":[105],"ground-truth":[110],"particular,":[113],"introduce":[115],"novel":[117],"Reference":[118],"Point":[119],"Distribution":[120],"Loss":[121],"(RPD-Loss)":[122],"ensure":[124],"converge":[127],"globally":[128],"toward":[129],"positions,":[131],"Scene-Adaptive":[134],"Refinement":[135],"head":[136],"(SAR-Head)":[137],"predicts":[139],"dynamic":[140],"offsets":[141],"each":[143],"point.":[145],"Both":[146],"components":[147],"can":[148],"be":[149],"seamlessly":[150],"integrated":[151],"into":[152],"mainstream":[153],"sparse":[154],"detectors.":[155],"Extensive":[156],"experiments":[157],"on":[158],"two":[159],"challenging":[160],"autonomous":[161],"driving":[162],"datasets":[163],"demonstrate":[164],"Refine3D":[166],"outperforms":[167],"state-of-the-art":[169],"improved":[171],"detection":[172],"accuracy":[173],"robustness.":[175]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2026-03-18T00:00:00"}
