{"id":"https://openalex.org/W4414359997","doi":"https://doi.org/10.24963/ijcai.2025/216","title":"BRIGHT-VO: Brightness-Guided Hybrid Transformer for Visual Odometry with Multi-modality Refinement Module","display_name":"BRIGHT-VO: Brightness-Guided Hybrid Transformer for Visual Odometry with Multi-modality Refinement Module","publication_year":2025,"publication_date":"2025-09-01","ids":{"openalex":"https://openalex.org/W4414359997","doi":"https://doi.org/10.24963/ijcai.2025/216"},"language":"en","primary_location":{"id":"doi:10.24963/ijcai.2025/216","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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/A5014005945","display_name":"Dongzhihan Wang","orcid":null},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Dongzhihan Wang","raw_affiliation_strings":["Shanghai University"],"affiliations":[{"raw_affiliation_string":"Shanghai University","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100397733","display_name":"Yang Yang","orcid":"https://orcid.org/0000-0003-1048-7994"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yang Yang","raw_affiliation_strings":["Shanghai University"],"affiliations":[{"raw_affiliation_string":"Shanghai University","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5089724481","display_name":"Xuyang Chen","orcid":"https://orcid.org/0009-0005-0160-744X"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xuyang Chen","raw_affiliation_strings":["Shanghai University"],"affiliations":[{"raw_affiliation_string":"Shanghai University","institution_ids":["https://openalex.org/I113940042"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5013028743","display_name":"Liang Xu","orcid":"https://orcid.org/0000-0001-7315-7306"},"institutions":[{"id":"https://openalex.org/I113940042","display_name":"Shanghai University","ror":"https://ror.org/006teas31","country_code":"CN","type":"education","lineage":["https://openalex.org/I113940042"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Liang Xu","raw_affiliation_strings":["Shanghai University"],"affiliations":[{"raw_affiliation_string":"Shanghai University","institution_ids":["https://openalex.org/I113940042"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5014005945"],"corresponding_institution_ids":["https://openalex.org/I113940042"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.26723594,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1936","last_page":"1944"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10638","display_name":"Optical measurement and interference techniques","score":0.9850999712944031,"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/T10638","display_name":"Optical measurement and interference techniques","score":0.9850999712944031,"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/T12153","display_name":"Advanced Optical Sensing Technologies","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/3105","display_name":"Instrumentation"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10191","display_name":"Robotics and Sensor-Based Localization","score":0.9829000234603882,"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/visual-odometry","display_name":"Visual odometry","score":0.7060999870300293},{"id":"https://openalex.org/keywords/pose","display_name":"Pose","score":0.6126999855041504},{"id":"https://openalex.org/keywords/odometry","display_name":"Odometry","score":0.6057999730110168},{"id":"https://openalex.org/keywords/orientation","display_name":"Orientation (vector space)","score":0.42809998989105225},{"id":"https://openalex.org/keywords/inertial-measurement-unit","display_name":"Inertial measurement unit","score":0.37619999051094055},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.36230000853538513},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.35690000653266907},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.3546999990940094},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.3495999872684479}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.798799991607666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7487000226974487},{"id":"https://openalex.org/C5799516","wikidata":"https://www.wikidata.org/wiki/Q4110915","display_name":"Visual odometry","level":3,"score":0.7060999870300293},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6992999911308289},{"id":"https://openalex.org/C52102323","wikidata":"https://www.wikidata.org/wiki/Q1671968","display_name":"Pose","level":2,"score":0.6126999855041504},{"id":"https://openalex.org/C49441653","wikidata":"https://www.wikidata.org/wiki/Q2014717","display_name":"Odometry","level":4,"score":0.6057999730110168},{"id":"https://openalex.org/C16345878","wikidata":"https://www.wikidata.org/wiki/Q107472979","display_name":"Orientation (vector space)","level":2,"score":0.42809998989105225},{"id":"https://openalex.org/C79061980","wikidata":"https://www.wikidata.org/wiki/Q941680","display_name":"Inertial measurement unit","level":2,"score":0.37619999051094055},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.36230000853538513},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.3546999990940094},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.3495999872684479},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.3488999903202057},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.34380000829696655},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3327000141143799},{"id":"https://openalex.org/C173386949","wikidata":"https://www.wikidata.org/wiki/Q192735","display_name":"Inertial frame of reference","level":2,"score":0.3118000030517578},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C34413123","wikidata":"https://www.wikidata.org/wiki/Q170978","display_name":"Robotics","level":3,"score":0.2994999885559082},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2953000068664551},{"id":"https://openalex.org/C123403432","wikidata":"https://www.wikidata.org/wiki/Q654068","display_name":"Visibility","level":2,"score":0.287200003862381},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.27649998664855957},{"id":"https://openalex.org/C39920418","wikidata":"https://www.wikidata.org/wiki/Q11476","display_name":"Kinematics","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.26330000162124634},{"id":"https://openalex.org/C198082294","wikidata":"https://www.wikidata.org/wiki/Q3399648","display_name":"Position (finance)","level":2,"score":0.25209999084472656}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.24963/ijcai.2025/216","is_oa":false,"landing_page_url":"https://doi.org/10.24963/ijcai.2025/216","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Thirty-Fourth International Joint Conference on Artificial Intelligence","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":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Visual":[0],"odometry":[1],"(VO)":[2],"plays":[3],"a":[4,23,81,100,136,143],"crucial":[5],"role":[6],"in":[7,34,57,104,157,185,189,195],"autonomous":[8],"driving,":[9],"robotic":[10],"navigation,":[11],"and":[12,20,48,67,127,131,152,173,193],"other":[13],"related":[14],"tasks":[15],"by":[16],"estimating":[17],"the":[18,62,68,105,150,170,174],"position":[19],"orientation":[21],"of":[22,61,65,71,145,154,183],"camera":[24,50],"based":[25,85],"on":[26,86,168],"visual":[27,94],"input.":[28],"Significant":[29],"progress":[30],"has":[31],"been":[32],"made":[33],"data-driven":[35],"VO":[36,83,155],"methods,":[37],"particularly":[38],"those":[39],"leveraging":[40],"deep":[41],"learning":[42],"techniques":[43],"to":[44,124,148],"extract":[45],"image":[46],"features":[47,66],"estimate":[49],"poses.":[51],"However,":[52],"these":[53],"methods":[54],"often":[55],"struggle":[56],"low-light":[58,138,196],"conditions":[59,147],"because":[60],"reduced":[63],"visibility":[64],"increased":[69],"difficulty":[70],"matching":[72],"keypoints.":[73],"To":[74],"address":[75],"this":[76,118],"limitation,":[77],"we":[78,134],"introduce":[79],"BrightVO,":[80],"novel":[82],"model":[84],"Transformer":[87],"architecture,":[88],"which":[89,141],"not":[90],"only":[91],"performs":[92],"front-end":[93],"feature":[95],"extraction,":[96],"but":[97],"also":[98],"incorporates":[99],"multi-modality":[101],"refinement":[102],"module":[103,119],"back-end":[106],"that":[107,163],"integrates":[108],"Inertial":[109],"Measurement":[110],"Unit":[111],"(IMU)":[112],"data.":[113],"Using":[114],"pose":[115,122,186],"graph":[116],"optimization,":[117],"iteratively":[120],"refines":[121],"estimates":[123],"reduce":[125],"errors":[126],"improve":[128],"both":[129,169],"accuracy":[130,188],"robustness.":[132],"Furthermore,":[133],"create":[135],"synthetic":[137],"dataset,":[139],"KiC4R,":[140],"includes":[142],"variety":[144],"lighting":[146],"facilitate":[149],"training":[151],"evaluation":[153],"frameworks":[156],"challenging":[158],"environments.":[159],"Experimental":[160],"results":[161],"demonstrate":[162],"BrightVO":[164],"achieves":[165],"state-of-the-art":[166],"performance":[167],"KiC4R":[171],"dataset":[172],"KITTI":[175],"benchmarks.":[176],"Specifically,":[177],"it":[178],"provides":[179],"an":[180],"average":[181],"improvement":[182],"20%":[184],"estimation":[187],"normal":[190],"outdoor":[191],"environments":[192],"25%":[194],"conditions,":[197],"outperforming":[198],"existing":[199],"methods.":[200],"This":[201],"work":[202],"is":[203],"open-source":[204],"at":[205],"https://github.com/Anastasiawd/BrightVO.":[206]},"counts_by_year":[],"updated_date":"2026-03-07T16:01:11.037858","created_date":"2025-10-10T00:00:00"}
