{"id":"https://openalex.org/W7166569101","doi":"https://doi.org/10.48550/arxiv.2606.27554","title":"Understanding Cross-Rig Generalization in Automotive Perception: a Multi-Rig Benchmark and Rig Variation Metrics","display_name":"Understanding Cross-Rig Generalization in Automotive Perception: a Multi-Rig Benchmark and Rig Variation Metrics","publication_year":2026,"publication_date":"2026-06-25","ids":{"openalex":"https://openalex.org/W7166569101","doi":"https://doi.org/10.48550/arxiv.2606.27554"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.27554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27554","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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.27554","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5138621574","display_name":"Tim Alexander Bader","orcid":"https://orcid.org/0009-0006-3391-277X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bader, Tim Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5091951403","display_name":"Tim Dieter Eberhardt","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Eberhardt, Tim Dieter","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5096521945","display_name":"Maximilian Dillitzer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Dillitzer, Maximilian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5067846212","display_name":"Wilhelm Stork","orcid":"https://orcid.org/0000-0003-0579-4615"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Stork, Wilhelm","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":false,"cited_by_count":0,"citation_normalized_percentile":null,"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.8751000165939331,"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"}},"topics":[{"id":"https://openalex.org/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.8751000165939331,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.021900000050663948,"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":0.018699999898672104,"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/benchmark","display_name":"Benchmark (surveying)","score":0.6427000164985657},{"id":"https://openalex.org/keywords/generalization","display_name":"Generalization","score":0.6330999732017517},{"id":"https://openalex.org/keywords/variation","display_name":"Variation (astronomy)","score":0.4851999878883362},{"id":"https://openalex.org/keywords/automotive-industry","display_name":"Automotive industry","score":0.45660001039505005},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.3711000084877014},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.34279999136924744},{"id":"https://openalex.org/keywords/ranking","display_name":"Ranking (information retrieval)","score":0.32440000772476196}],"concepts":[{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6427000164985657},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.6330999732017517},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5881999731063843},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5198000073432922},{"id":"https://openalex.org/C2778334786","wikidata":"https://www.wikidata.org/wiki/Q1586270","display_name":"Variation (astronomy)","level":2,"score":0.4851999878883362},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.474700003862381},{"id":"https://openalex.org/C526921623","wikidata":"https://www.wikidata.org/wiki/Q190117","display_name":"Automotive industry","level":2,"score":0.45660001039505005},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.3711000084877014},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.34279999136924744},{"id":"https://openalex.org/C189430467","wikidata":"https://www.wikidata.org/wiki/Q7293293","display_name":"Ranking (information retrieval)","level":2,"score":0.32440000772476196},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3188999891281128},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.311599999666214},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.29899999499320984},{"id":"https://openalex.org/C7305733","wikidata":"https://www.wikidata.org/wiki/Q207961","display_name":"Geometric shape","level":2,"score":0.28139999508857727},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.2669999897480011},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C195766429","wikidata":"https://www.wikidata.org/wiki/Q394","display_name":"Metrology","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.25529998540878296},{"id":"https://openalex.org/C184898388","wikidata":"https://www.wikidata.org/wiki/Q1435712","display_name":"Pairwise comparison","level":2,"score":0.25200000405311584}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.27554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27554","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":"doi:10.48550/arxiv.2606.27554","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.27554","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":false,"raw_source_name":null,"raw_type":"Preprint"},"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":{"Camera-based":[0],"perception":[1,100],"systems":[2],"for":[3,164],"autonomous":[4],"driving":[5,65],"are":[6],"typically":[7],"developed":[8],"and":[9,29,102,132,155],"evaluated":[10],"using":[11],"fixed":[12],"sensor":[13,169],"rigs,":[14],"while":[15],"real-world":[16],"vehicle":[17],"fleets":[18],"exhibit":[19],"substantial":[20,104],"variation":[21],"in":[22,39,84],"camera":[23,30,71],"placement,":[24],"orientation,":[25],"field":[26],"of":[27,78,97],"view,":[28],"count.":[31],"This":[32,73],"mismatch":[33],"introduces":[34],"a":[35,60,161],"cross-rig":[36,79,94,152],"domain":[37],"gap":[38],"which":[40],"only":[41],"the":[42,90],"geometric":[43,109,137,145],"observation":[44],"process":[45],"changes.":[46],"To":[47,112],"study":[48],"this":[49],"effect":[50],"under":[51,67],"controlled":[52],"conditions,":[53],"we":[54,92,116],"introduce":[55,118],"Plentiful":[56],"CARLA":[57],"Camera":[58],"Rigs,":[59],"benchmark":[61],"that":[62,144,156],"renders":[63],"identical":[64],"scenes":[66],"14":[68],"systematically":[69],"designed":[70],"rigs.":[72,140,170],"setup":[74],"enables":[75],"direct":[76],"analysis":[77],"generalization":[80],"without":[81],"confounding":[82],"changes":[83],"scene":[85],"content":[86],"or":[87],"appearance.":[88],"Using":[89],"benchmark,":[91],"analyze":[93],"transfer":[95,166],"behavior":[96],"representative":[98],"multi-view":[99],"architectures":[101],"observe":[103],"performance":[105,153],"shifts":[106,154],"induced":[107],"by":[108],"rig":[110,124,130,146],"variation.":[111],"facilitate":[113],"structured":[114],"analysis,":[115],"further":[117],"two":[119],"calibration-based":[120],"descriptors":[121],"derived":[122],"from":[123],"metadata:":[125],"Rig":[126,133,157],"Variance,":[127],"capturing":[128],"internal":[129],"diversity,":[131],"Contrastive":[134,158],"Distance,":[135],"measuring":[136],"discrepancy":[138],"between":[139,168],"Our":[141],"experiments":[142],"show":[143],"differences":[147],"strongly":[148],"correlate":[149],"with":[150],"relative":[151],"Distance":[159],"provides":[160],"reliable":[162],"proxy":[163],"ranking":[165],"difficulty":[167]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-06-30T00:00:00"}