{"id":"https://openalex.org/W4400650188","doi":"https://doi.org/10.1109/iv55156.2024.10588584","title":"ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions","display_name":"ContextualFusion: Context-Based Multi-Sensor Fusion for 3D Object Detection in Adverse Operating Conditions","publication_year":2024,"publication_date":"2024-06-02","ids":{"openalex":"https://openalex.org/W4400650188","doi":"https://doi.org/10.1109/iv55156.2024.10588584"},"language":"en","primary_location":{"id":"doi:10.1109/iv55156.2024.10588584","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588584","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5092850531","display_name":"Shounak Sural","orcid":"https://orcid.org/0009-0007-6537-8716"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Shounak Sural","raw_affiliation_strings":["Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068398736","display_name":"Nishad Sahu","orcid":"https://orcid.org/0000-0002-0536-4538"},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Nishad Sahu","raw_affiliation_strings":["Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5104053889","display_name":"Ragunathan Rajkumar","orcid":null},"institutions":[{"id":"https://openalex.org/I74973139","display_name":"Carnegie Mellon University","ror":"https://ror.org/05x2bcf33","country_code":"US","type":"education","lineage":["https://openalex.org/I74973139"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ragunathan Raj Rajkumar","raw_affiliation_strings":["Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213"],"affiliations":[{"raw_affiliation_string":"Carnegie Mellon University,Department of Electrical and Computer Engineering,Pittsburgh,PA,USA,15213","institution_ids":["https://openalex.org/I74973139"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5092850531"],"corresponding_institution_ids":["https://openalex.org/I74973139"],"apc_list":null,"apc_paid":null,"fwci":2.4745,"has_fulltext":false,"cited_by_count":10,"citation_normalized_percentile":{"value":0.9031746,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"1534","last_page":"1541"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.9484999775886536,"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":0.9484999775886536,"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":0.9089000225067139,"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/computer-science","display_name":"Computer science","score":0.660910964012146},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.628291130065918},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.5764812231063843},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.5450681447982788},{"id":"https://openalex.org/keywords/object-detection","display_name":"Object detection","score":0.4758548438549042},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4164170026779175},{"id":"https://openalex.org/keywords/computer-vision","display_name":"Computer vision","score":0.3677794933319092},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.35032111406326294},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.15678954124450684}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.660910964012146},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.628291130065918},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.5764812231063843},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.5450681447982788},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.4758548438549042},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4164170026779175},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.3677794933319092},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.35032111406326294},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.15678954124450684},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iv55156.2024.10588584","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iv55156.2024.10588584","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE Intelligent Vehicles Symposium (IV)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W1869778509","https://openalex.org/W2119857623","https://openalex.org/W2150066425","https://openalex.org/W2155511848","https://openalex.org/W2555618208","https://openalex.org/W2615547864","https://openalex.org/W2727840223","https://openalex.org/W2963727135","https://openalex.org/W2991167156","https://openalex.org/W3034543232","https://openalex.org/W3035574168","https://openalex.org/W3049255424","https://openalex.org/W3133719020","https://openalex.org/W3138516171","https://openalex.org/W3163545977","https://openalex.org/W3167095230","https://openalex.org/W3170030651","https://openalex.org/W3196813118","https://openalex.org/W3212920938","https://openalex.org/W4226305814","https://openalex.org/W4293112749","https://openalex.org/W4312707458","https://openalex.org/W4382240183","https://openalex.org/W4383066393","https://openalex.org/W4385301252","https://openalex.org/W4391769656","https://openalex.org/W6639086533","https://openalex.org/W6745896446","https://openalex.org/W6745935785","https://openalex.org/W6800446943","https://openalex.org/W6811230113","https://openalex.org/W6842385943"],"related_works":["https://openalex.org/W2737719445","https://openalex.org/W2099421762","https://openalex.org/W2132659060","https://openalex.org/W2031992971","https://openalex.org/W3214791684","https://openalex.org/W2353265673","https://openalex.org/W2031175860","https://openalex.org/W4292830139","https://openalex.org/W4319309705","https://openalex.org/W2152662039"],"abstract_inverted_index":{"The":[0],"fusion":[1,48,120],"of":[2,22,31,121,152,169,199],"multimodal":[3,143],"sensor":[4,122],"data":[5],"streams":[6,123],"such":[7],"as":[8],"camera":[9],"images":[10],"and":[11,34,58,72,95,101,159],"lidar":[12],"point":[13],"clouds":[14],"plays":[15],"an":[16,166],"important":[17],"role":[18],"in":[19,56,68,131],"the":[20,90,119,126,136,150,190],"operation":[21],"autonomous":[23],"vehicles":[24],"(AVs).":[25],"Robust":[26],"perception":[27,55],"across":[28,99],"a":[29,65,81,112,142,195],"range":[30],"adverse":[32],"weather":[33,60,74,102],"lighting":[35,100],"conditions":[36],"is":[37],"specifically":[38],"required":[39],"for":[40,54,118],"AVs":[41],"to":[42,88,140,148],"be":[43],"deployed":[44],"widely.":[45],"While":[46],"multi-sensor":[47],"networks":[49],"have":[50],"been":[51],"previously":[52],"developed":[53],"sunny":[57],"clear":[59],"conditions,":[61],"these":[62],"methods":[63,173],"show":[64],"significant":[66,196],"degradation":[67],"performance":[69,186],"under":[70],"night-time":[71],"poor":[73],"conditions.":[75,161],"In":[76],"this":[77],"paper,":[78],"we":[79,110,134],"propose":[80],"simple":[82],"yet":[83],"effective":[84],"technique":[85],"called":[86,146],"ContextualFusion":[87,163],"incorporate":[89],"domain":[91],"knowledge":[92],"about":[93],"cameras":[94],"lidars":[96],"behaving":[97],"differently":[98],"variations":[103],"into":[104],"3D":[105,184],"object":[106],"detection":[107],"models.":[108],"Specifically,":[109],"design":[111],"Gated":[113],"Convolutional":[114],"Fusion":[115],"(GatedConv)":[116],"approach":[117,164],"based":[124],"on":[125,174,189],"operational":[127],"context.":[128],"To":[129],"aid":[130],"our":[132,175,180],"evaluation,":[133],"use":[135],"open-source":[137],"simulator":[138],"CARLA":[139],"create":[141],"adverse-condition":[144],"dataset":[145,193],"AdverseOp3D":[147],"address":[149],"shortcomings":[151],"existing":[153],"datasets":[154],"being":[155],"biased":[156],"towards":[157],"daytime":[158],"good-weather":[160],"Our":[162],"yields":[165],"mAP":[167,197],"improvement":[168,198],"6.2%":[170],"over":[171],"state-of-the-art":[172,183],"context-balanced":[176],"synthetic":[177],"dataset.":[178],"Finally,":[179],"method":[181],"enhances":[182],"objection":[185],"at":[187],"night":[188],"real-world":[191],"NuScenes":[192],"with":[194],"11.7%.":[200]},"counts_by_year":[{"year":2026,"cited_by_count":2},{"year":2025,"cited_by_count":7},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-02T15:55:50.835912","created_date":"2025-10-10T00:00:00"}