{"id":"https://openalex.org/W7159660440","doi":"https://doi.org/10.48550/arxiv.2604.27499","title":"Towards All-Day Perception for Off-Road Driving: A Large-Scale Multispectral Dataset and Comprehensive Benchmark","display_name":"Towards All-Day Perception for Off-Road Driving: A Large-Scale Multispectral Dataset and Comprehensive Benchmark","publication_year":2026,"publication_date":"2026-04-30","ids":{"openalex":"https://openalex.org/W7159660440","doi":"https://doi.org/10.48550/arxiv.2604.27499"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.27499","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27499","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.2604.27499","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5134956166","display_name":"Shuo Wang","orcid":"https://orcid.org/0000-0002-7990-7515"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shuo","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134962319","display_name":"Jilin Mei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mei, Jilin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102526350","display_name":"Wenfei Guan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Guan, Wenfei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134971724","display_name":"Shuai Wang (109515)","orcid":"https://orcid.org/0000-0003-3407-9143"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Shuai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134958200","display_name":"Yan Xing","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Xing, Yan","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5134974198","display_name":"Chen Min","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Min, Chen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5134991395","display_name":"Yu Hu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Yu","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":0.3082999885082245,"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":0.3082999885082245,"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/T11963","display_name":"Impact of Light on Environment and Health","score":0.10729999840259552,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental 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":0.10540000349283218,"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":0.6650999784469604},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6019999980926514},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.5565999746322632},{"id":"https://openalex.org/keywords/initialization","display_name":"Initialization","score":0.4147999882698059},{"id":"https://openalex.org/keywords/modalities","display_name":"Modalities","score":0.41359999775886536},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.41280001401901245},{"id":"https://openalex.org/keywords/multispectral-image","display_name":"Multispectral image","score":0.3833000063896179},{"id":"https://openalex.org/keywords/key","display_name":"Key (lock)","score":0.3555000126361847}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7196000218391418},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6650999784469604},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6298999786376953},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6019999980926514},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.5565999746322632},{"id":"https://openalex.org/C114466953","wikidata":"https://www.wikidata.org/wiki/Q6034165","display_name":"Initialization","level":2,"score":0.4147999882698059},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.41280001401901245},{"id":"https://openalex.org/C173163844","wikidata":"https://www.wikidata.org/wiki/Q1761440","display_name":"Multispectral image","level":2,"score":0.3833000063896179},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.3555000126361847},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.35199999809265137},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.34540000557899475},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.322299987077713},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3188000023365021},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.29600000381469727},{"id":"https://openalex.org/C177148314","wikidata":"https://www.wikidata.org/wiki/Q170084","display_name":"Generalization","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.2700999975204468},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.26739999651908875},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2614000141620636},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.25369998812675476}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.27499","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27499","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.2604.27499","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.27499","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":[{"display_name":"Sustainable cities and communities","id":"https://metadata.un.org/sdg/11","score":0.745525062084198}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Off-road":[0],"nighttime":[1,70],"autonomous":[2,166],"driving":[3,167],"suffers":[4],"from":[5],"unreliable":[6],"visible-light":[7],"perception,":[8],"making":[9],"infrared":[10,27,56,78,172],"modality":[11],"crucial":[12],"for":[13,58,69,102,162],"accurate":[14],"freespace":[15,61,104],"detection.":[16],"However,":[17],"progress":[18],"remains":[19],"limited":[20],"due":[21],"to":[22,35,49,148],"the":[23,31,45,53],"scarcity":[24],"of":[25],"annotated":[26,77],"off-road":[28,59,165],"datasets":[29],"and":[30,87,118,135,153,168,177],"inter-frame":[32,108],"inconsistencies":[33,109],"inherent":[34],"current":[36],"single-frame":[37],"methods.":[38],"To":[39],"address":[40],"these":[41],"gaps,":[42],"we":[43,95],"present":[44],"IRON":[46,126,178],"dataset,":[47,94,127],"which,":[48],"our":[50,125,157],"knowledge,":[51],"is":[52],"first":[54],"large-scale":[55],"dataset":[57,73,179],"temporal":[60,103,173],"detection":[62,105],"under":[63],"all-day":[64,164],"conditions,":[65],"with":[66,80],"strong":[67],"support":[68],"perception.":[71,174],"The":[72,175],"comprises":[74],"24,314":[75],"densely":[76],"images":[79,83],"synchronized":[81],"RGB":[82,149],"in":[84,171],"diverse":[85],"scenes":[86],"different":[88],"light":[89],"conditions.":[90],"Building":[91],"upon":[92],"this":[93],"propose":[96],"IRONet,":[97],"a":[98,115,119,160],"novel":[99],"flow-free":[100],"framework":[101],"that":[106],"addresses":[107],"by":[110],"aggregating":[111],"historical":[112],"context":[113],"via":[114],"memory-attention":[116],"mechanism":[117],"carefully":[120],"designed":[121],"mask":[122],"decoder.":[123],"On":[124],"IRONet":[128,143],"achieves":[129],"state-of-the-art":[130],"performance,":[131],"reaching":[132],"82.93%(+1.19%)":[133],"IoU":[134],"90.66%(+0.71%)":[136],"F1":[137],"score":[138],"at":[139,182],"real-time":[140],"inference.":[141],"Remarkably,":[142],"also":[144],"exhibits":[145],"robust":[146],"generalization":[147],"modalities":[150],"on":[151],"ORFD":[152],"Rellis":[154],"datasets.":[155],"Overall,":[156],"work":[158],"establishes":[159],"foundation":[161],"reliable":[163],"future":[169],"research":[170],"code":[176],"are":[180],"available":[181],"https://github.com/wsnbws/IRON.":[183]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-02T00:00:00"}