{"id":"https://openalex.org/W7154608622","doi":"https://doi.org/10.48550/arxiv.2604.13426","title":"Event-Adaptive State Transition and Gated Fusion for RGB-Event Object Tracking","display_name":"Event-Adaptive State Transition and Gated Fusion for RGB-Event Object Tracking","publication_year":2026,"publication_date":"2026-04-15","ids":{"openalex":"https://openalex.org/W7154608622","doi":"https://doi.org/10.48550/arxiv.2604.13426"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.13426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13426","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":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.13426","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5037442437","display_name":"Jinlin You","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"You, Jinlin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133811320","display_name":"Muyu Li","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Li, Muyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5133777070","display_name":"Xudong Zhao","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhao, Xudong","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":3,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.3603000044822693,"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/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.3603000044822693,"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/T13553","display_name":"Age of Information Optimization","score":0.1370999962091446,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.054099999368190765,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.527400016784668},{"id":"https://openalex.org/keywords/fusion","display_name":"Fusion","score":0.45669999718666077},{"id":"https://openalex.org/keywords/overfitting","display_name":"Overfitting","score":0.4361000061035156},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.4277999997138977},{"id":"https://openalex.org/keywords/robustness","display_name":"Robustness (evolution)","score":0.42340001463890076},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.4142000079154968},{"id":"https://openalex.org/keywords/tracking","display_name":"Tracking (education)","score":0.4108999967575073},{"id":"https://openalex.org/keywords/fusion-mechanism","display_name":"Fusion mechanism","score":0.3937999904155731},{"id":"https://openalex.org/keywords/snapshot","display_name":"Snapshot (computer storage)","score":0.3815000057220459}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.597599983215332},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5656999945640564},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5403000116348267},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.527400016784668},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.45669999718666077},{"id":"https://openalex.org/C22019652","wikidata":"https://www.wikidata.org/wiki/Q331309","display_name":"Overfitting","level":3,"score":0.4361000061035156},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.4277999997138977},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.42340001463890076},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.4142000079154968},{"id":"https://openalex.org/C2775936607","wikidata":"https://www.wikidata.org/wiki/Q466845","display_name":"Tracking (education)","level":2,"score":0.4108999967575073},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.3937999904155731},{"id":"https://openalex.org/C55282118","wikidata":"https://www.wikidata.org/wiki/Q252683","display_name":"Snapshot (computer storage)","level":2,"score":0.3815000057220459},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.36169999837875366},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3594000041484833},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.35659998655319214},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3449999988079071},{"id":"https://openalex.org/C189950617","wikidata":"https://www.wikidata.org/wiki/Q937228","display_name":"Property (philosophy)","level":2,"score":0.3361000120639801},{"id":"https://openalex.org/C2777798563","wikidata":"https://www.wikidata.org/wiki/Q7603916","display_name":"State vector","level":2,"score":0.3319999873638153},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.30230000615119934},{"id":"https://openalex.org/C49555168","wikidata":"https://www.wikidata.org/wiki/Q176583","display_name":"Stochastic matrix","level":3,"score":0.29319998621940613},{"id":"https://openalex.org/C202474056","wikidata":"https://www.wikidata.org/wiki/Q1931635","display_name":"Video tracking","level":3,"score":0.2921000123023987},{"id":"https://openalex.org/C79403827","wikidata":"https://www.wikidata.org/wiki/Q3988","display_name":"Real-time computing","level":1,"score":0.28700000047683716},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C154586513","wikidata":"https://www.wikidata.org/wiki/Q4420972","display_name":"Tracking system","level":3,"score":0.27489998936653137},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.2709999978542328},{"id":"https://openalex.org/C57493831","wikidata":"https://www.wikidata.org/wiki/Q3134666","display_name":"Projection (relational algebra)","level":2,"score":0.2687999904155731},{"id":"https://openalex.org/C160343418","wikidata":"https://www.wikidata.org/wiki/Q185256","display_name":"Rigidity (electromagnetism)","level":2,"score":0.2671999931335449},{"id":"https://openalex.org/C57691317","wikidata":"https://www.wikidata.org/wiki/Q1289248","display_name":"Scalar (mathematics)","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2653000056743622}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.13426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13426","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":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2604.13426","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.13426","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":"article"},"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":{"Existing":[0],"Vision":[1],"Mamba-based":[2],"RGB-Event(RGBE)":[3],"tracking":[4,50],"methods":[5],"suffer":[6],"from":[7,126],"using":[8],"static":[9],"state":[10,68,75,88],"transition":[11,69,76],"matrices,":[12],"which":[13],"fail":[14],"to":[15,17,25],"adapt":[16],"variations":[18],"in":[19],"event":[20,29,80,98,119,127],"sparsity.":[21],"This":[22,112],"rigidity":[23],"leads":[24],"imbalanced":[26],"modeling-underfitting":[27],"sparse":[28,95],"streams":[30],"and":[31,48,96,122,129,156],"overfitting":[32],"dense":[33,97],"ones-thus":[34],"degrading":[35],"cross-modal":[36,110],"fusion":[37,138],"robustness.":[38],"To":[39],"address":[40],"these":[41],"limitations,":[42],"we":[43,64,101],"propose":[44],"MambaTrack,":[45],"a":[46,54,103],"multimodal":[47],"efficient":[49],"framework":[51],"built":[52],"upon":[53],"Dynamic":[55],"State":[56],"Space":[57],"Model(DSSM).":[58],"Our":[59],"contributions":[60],"are":[61],"twofold.":[62],"First,":[63],"introduce":[65],"an":[66],"event-adaptive":[67],"mechanism":[70],"that":[71,148],"dynamically":[72],"modulates":[73],"the":[74,87,118,137,154],"matrix":[77],"based":[78],"on":[79,153],"stream":[81],"density.":[82],"A":[83],"learnable":[84],"scalar":[85],"governs":[86],"evolution":[89],"rate,":[90],"enabling":[91],"differentiated":[92],"modeling":[93],"of":[94],"flows.":[99],"Second,":[100],"develop":[102],"Gated":[104],"Projection":[105],"Fusion(GPF)":[106],"module":[107,113],"for":[108,164],"robust":[109],"integration.":[111],"projects":[114],"RGB":[115,130],"features":[116],"into":[117],"feature":[120],"space":[121],"generates":[123],"adaptive":[124],"gates":[125,134],"density":[128],"confidence":[131],"scores.":[132],"These":[133],"precisely":[135],"control":[136],"intensity,":[139],"suppressing":[140],"noise":[141],"while":[142],"preserving":[143],"complementary":[144],"information.":[145],"Experiments":[146],"show":[147],"MambaTrack":[149],"achieves":[150],"state-of-the-art":[151],"performance":[152],"FE108":[155],"FELT":[157],"datasets.":[158],"Its":[159],"lightweight":[160],"design":[161],"suggests":[162],"potential":[163],"real-time":[165],"embedded":[166],"deployment.":[167]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2026-04-17T00:00:00"}