{"id":"https://openalex.org/W7134818805","doi":"https://doi.org/10.48550/arxiv.2603.08611","title":"FOMO-3D: Using Vision Foundation Models for Long-Tailed 3D Object Detection","display_name":"FOMO-3D: Using Vision Foundation Models for Long-Tailed 3D Object Detection","publication_year":2026,"publication_date":"2026-03-09","ids":{"openalex":"https://openalex.org/W7134818805","doi":"https://doi.org/10.48550/arxiv.2603.08611"},"language":null,"primary_location":{"id":"pmh:doi:10.48550/arxiv.2603.08611","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"type":"article","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":null,"any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5007577768","display_name":"Anqi Yang","orcid":"https://orcid.org/0000-0003-0811-7951"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yang, Anqi Joyce","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5000380827","display_name":"James Tu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tu, James","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003458137","display_name":"Nikita Dvornik","orcid":"https://orcid.org/0000-0003-4770-3427"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dvornik, Nikita","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5046938597","display_name":"Enxu Li","orcid":"https://orcid.org/0009-0000-4113-8864"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Enxu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5010469348","display_name":"Raquel Urtasun","orcid":"https://orcid.org/0000-0003-2332-5361"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Urtasun, Raquel","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":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.27862576,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/T10036","display_name":"Advanced Neural Network Applications","score":0.8582000136375427,"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":0.8582000136375427,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.07660000026226044,"subfield":{"id":"https://openalex.org/subfields/2203","display_name":"Automotive 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":0.014100000262260437,"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/leverage","display_name":"Leverage (statistics)","score":0.7506999969482422},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.6866999864578247},{"id":"https://openalex.org/keywords/prior-probability","display_name":"Prior probability","score":0.6696000099182129},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.5353000164031982},{"id":"https://openalex.org/keywords/foundation","display_name":"Foundation (evidence)","score":0.48890000581741333},{"id":"https://openalex.org/keywords/economic-shortage","display_name":"Economic shortage","score":0.4648999869823456},{"id":"https://openalex.org/keywords/training-set","display_name":"Training set","score":0.39399999380111694},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3889000117778778}],"concepts":[{"id":"https://openalex.org/C153083717","wikidata":"https://www.wikidata.org/wiki/Q6535263","display_name":"Leverage (statistics)","level":2,"score":0.7506999969482422},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.6866999864578247},{"id":"https://openalex.org/C177769412","wikidata":"https://www.wikidata.org/wiki/Q278090","display_name":"Prior probability","level":3,"score":0.6696000099182129},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6565999984741211},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.635699987411499},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.5353000164031982},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.49459999799728394},{"id":"https://openalex.org/C2780966255","wikidata":"https://www.wikidata.org/wiki/Q5474306","display_name":"Foundation (evidence)","level":2,"score":0.48890000581741333},{"id":"https://openalex.org/C194051981","wikidata":"https://www.wikidata.org/wiki/Q1337691","display_name":"Economic shortage","level":3,"score":0.4648999869823456},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.40560001134872437},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3889000117778778},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.35530000925064087},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.319599986076355},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.31540000438690186},{"id":"https://openalex.org/C90312973","wikidata":"https://www.wikidata.org/wiki/Q7449052","display_name":"Semantic data model","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C94915269","wikidata":"https://www.wikidata.org/wiki/Q1834857","display_name":"Detector","level":2,"score":0.27219998836517334},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.2667999863624573},{"id":"https://openalex.org/C3019007443","wikidata":"https://www.wikidata.org/wiki/Q568742","display_name":"3d model","level":2,"score":0.2635999917984009},{"id":"https://openalex.org/C2983685735","wikidata":"https://www.wikidata.org/wiki/Q5227355","display_name":"Data source","level":2,"score":0.2628999948501587},{"id":"https://openalex.org/C87833898","wikidata":"https://www.wikidata.org/wiki/Q1060280","display_name":"Advanced driver assistance systems","level":2,"score":0.25679999589920044},{"id":"https://openalex.org/C160920958","wikidata":"https://www.wikidata.org/wiki/Q7662746","display_name":"Synthetic data","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:doi:10.48550/arxiv.2603.08611","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},{"id":"doi:10.48550/arxiv.2603.08611","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.08611","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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:doi:10.48550/arxiv.2603.08611","is_oa":true,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4406922384","display_name":"Open MIND","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"publisher-specific-oa","license_id":"https://openalex.org/licenses/publisher-specific-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Article"},"sustainable_development_goals":[{"score":0.6939383149147034,"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,15,37,71,82,127,152],"navigate":[3],"complex":[4],"traffic":[5,20,34],"environments,":[6],"self-driving":[7],"vehicles":[8],"must":[9],"recognize":[10],"many":[11,24],"semantic":[12,95],"classes":[13],"pertaining":[14],"vulnerable":[16],"road":[17],"users":[18],"or":[19],"control":[21],"devices.":[22],"However,":[23],"safety-critical":[25],"objects":[26],"(e.g.,":[27],"construction":[28],"worker)":[29],"appear":[30],"infrequently":[31],"in":[32],"nominal":[33],"conditions,":[35],"leading":[36],"a":[38,56,64,104,113,117],"severe":[39],"shortage":[40],"of":[41,59,67],"training":[42],"examples":[43],"from":[44,99,130,142],"driving":[45,135],"data":[46,136],"alone.":[47],"Recent":[48],"vision":[49,84,143],"foundation":[50,85,144],"models,":[51],"which":[52],"are":[53],"trained":[54],"on":[55,133],"large":[57,153],"corpus":[58],"data,":[60],"can":[61],"serve":[62],"as":[63],"good":[65],"source":[66],"external":[68],"prior":[69],"knowledge":[70],"improve":[72],"generalization.":[73],"We":[74],"propose":[75],"FOMO-3D,":[76],"the":[77],"first":[78,109],"multi-modal":[79,148],"3D":[80,89,157],"detector":[81],"leverage":[83],"models":[86,145],"for":[87,155],"long-tailed":[88,156],"detection.":[90,158],"Specifically,":[91],"FOMO-3D":[92],"exploits":[93],"rich":[94,140],"and":[96,101,116,121],"depth":[97],"priors":[98,141],"OWLv2":[100],"Metric3Dv2":[102],"within":[103],"two-stage":[105],"detection":[106],"paradigm":[107],"that":[108,138],"generates":[110],"proposals":[111],"with":[112,124,146],"LiDAR-based":[114],"branch":[115],"novel":[118],"camera-based":[119],"branch,":[120],"refines":[122],"them":[123],"attention":[125],"especially":[126],"image":[128],"features":[129],"OWL.":[131],"Evaluations":[132],"real-world":[134],"show":[137],"using":[139],"careful":[147],"fusion":[149],"designs":[150],"leads":[151],"gains":[154],"Project":[159],"website":[160],"is":[161],"at":[162],"https://waabi.ai/fomo3d/.":[163]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-03-11T00:00:00"}
