{"id":"https://openalex.org/W7161983740","doi":"https://doi.org/10.48550/arxiv.2605.21308","title":"Deformba: Vision State Space Model with Adaptive State Fusion","display_name":"Deformba: Vision State Space Model with Adaptive State Fusion","publication_year":2026,"publication_date":"2026-05-20","ids":{"openalex":"https://openalex.org/W7161983740","doi":"https://doi.org/10.48550/arxiv.2605.21308"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.21308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21308","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.2605.21308","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5031528341","display_name":"Hongyu Ke","orcid":"https://orcid.org/0009-0003-5653-9814"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ke, Hongyu","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136655726","display_name":"Jack Morris","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Morris, Jack","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136712042","display_name":"Yongkang Liu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Yongkang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5120581937","display_name":"Satoshi Kitai","orcid":"https://orcid.org/0009-0006-6395-2502"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kitai, Satoshi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136723236","display_name":"Kentaro Oguchi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Oguchi, Kentaro","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136675514","display_name":"Yi Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ding, Yi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136689564","display_name":"Haoxin Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Haoxin","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/T10036","display_name":"Advanced Neural Network Applications","score":0.17339999973773956,"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":0.17339999973773956,"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/T11689","display_name":"Adversarial Robustness in Machine Learning","score":0.10119999945163727,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"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/T11099","display_name":"Autonomous Vehicle Technology and Safety","score":0.09799999743700027,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5432999730110168},{"id":"https://openalex.org/keywords/machine-vision","display_name":"Machine vision","score":0.4999000132083893},{"id":"https://openalex.org/keywords/sequence","display_name":"Sequence (biology)","score":0.476500004529953},{"id":"https://openalex.org/keywords/object","display_name":"Object (grammar)","score":0.4713999927043915},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.4643000066280365},{"id":"https://openalex.org/keywords/sensor-fusion","display_name":"Sensor fusion","score":0.4180000126361847},{"id":"https://openalex.org/keywords/cognitive-neuroscience-of-visual-object-recognition","display_name":"Cognitive neuroscience of visual object recognition","score":0.3783000111579895},{"id":"https://openalex.org/keywords/human-visual-system-model","display_name":"Human visual system model","score":0.35100001096725464},{"id":"https://openalex.org/keywords/state","display_name":"State (computer science)","score":0.3474999964237213}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6711999773979187},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6686999797821045},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6039000153541565},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5432999730110168},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.4999000132083893},{"id":"https://openalex.org/C2778112365","wikidata":"https://www.wikidata.org/wiki/Q3511065","display_name":"Sequence (biology)","level":2,"score":0.476500004529953},{"id":"https://openalex.org/C2781238097","wikidata":"https://www.wikidata.org/wiki/Q175026","display_name":"Object (grammar)","level":2,"score":0.4713999927043915},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.4643000066280365},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.4180000126361847},{"id":"https://openalex.org/C64876066","wikidata":"https://www.wikidata.org/wiki/Q5141226","display_name":"Cognitive neuroscience of visual object recognition","level":3,"score":0.3783000111579895},{"id":"https://openalex.org/C160086991","wikidata":"https://www.wikidata.org/wiki/Q5939193","display_name":"Human visual system model","level":3,"score":0.35100001096725464},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.3474999964237213},{"id":"https://openalex.org/C173414695","wikidata":"https://www.wikidata.org/wiki/Q5510276","display_name":"Fusion mechanism","level":4,"score":0.34619998931884766},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.3359000086784363},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.3357999920845032},{"id":"https://openalex.org/C178253425","wikidata":"https://www.wikidata.org/wiki/Q162668","display_name":"Visual perception","level":3,"score":0.3188999891281128},{"id":"https://openalex.org/C69744172","wikidata":"https://www.wikidata.org/wiki/Q860822","display_name":"Image fusion","level":3,"score":0.31540000438690186},{"id":"https://openalex.org/C183322885","wikidata":"https://www.wikidata.org/wiki/Q17007702","display_name":"Context model","level":3,"score":0.31450000405311584},{"id":"https://openalex.org/C9417928","wikidata":"https://www.wikidata.org/wiki/Q1070689","display_name":"Image processing","level":3,"score":0.295199990272522},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.289900004863739},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.2833999991416931},{"id":"https://openalex.org/C66024118","wikidata":"https://www.wikidata.org/wiki/Q1122506","display_name":"Computational model","level":2,"score":0.2799000144004822},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2759000062942505},{"id":"https://openalex.org/C2776151529","wikidata":"https://www.wikidata.org/wiki/Q3045304","display_name":"Object detection","level":3,"score":0.26809999346733093},{"id":"https://openalex.org/C166704113","wikidata":"https://www.wikidata.org/wiki/Q861092","display_name":"Image registration","level":3,"score":0.26460000872612},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2628999948501587},{"id":"https://openalex.org/C108882727","wikidata":"https://www.wikidata.org/wiki/Q2991685","display_name":"Solid modeling","level":2,"score":0.258899986743927},{"id":"https://openalex.org/C139807058","wikidata":"https://www.wikidata.org/wiki/Q352374","display_name":"Adaptation (eye)","level":2,"score":0.2587999999523163},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.25459998846054077},{"id":"https://openalex.org/C193611912","wikidata":"https://www.wikidata.org/wiki/Q4677596","display_name":"Active vision","level":2,"score":0.2517000138759613}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.21308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21308","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.2605.21308","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.21308","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":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"State":[0],"Space":[1],"Models":[2],"(SSMs)":[3],"have":[4],"emerged":[5],"as":[6,105,161,168,170],"a":[7,78,116],"powerful":[8],"and":[9,17,53,84,146,166],"efficient":[10],"alternative":[11],"to":[12,25,42],"Transformers,":[13],"demonstrating":[14],"linear-time":[15],"complexity":[16,131],"exceptional":[18],"sequence":[19,92],"modeling":[20,93],"capabilities.":[21],"However,":[22],"their":[23],"application":[24],"vision":[26,32,62,158,172],"tasks":[27,103,159,173],"remains":[28],"challenging.":[29],"First,":[30],"existing":[31],"SSMs":[33,63,88],"largely":[34],"depend":[35],"on":[36,155],"manually":[37],"designed":[38,89],"fixed":[39],"scanning":[40],"methods":[41],"flatten":[43],"image":[44,162],"patches":[45],"into":[46],"sequences,":[47],"which":[48],"imposes":[49],"predefined":[50],"geometric":[51],"structures":[52],"increases":[54],"the":[55,58,81,123,129,144],"complexity.":[56],"Second,":[57],"broader":[59],"adoption":[60],"of":[61,80,87,132,149],"is":[64,77,98],"hindered":[65],"in":[66],"domains":[67],"that":[68,120,180],"require":[69],"query-based":[70],"interactions":[71],"between":[72],"distinct":[73],"information":[74,126],"streams.":[75],"This":[76,95],"result":[79],"inherently":[82],"causal":[83],"self-referential":[85],"nature":[86],"for":[90,100],"1D":[91],"tasks.":[94],"fusion":[96,138],"mechanism":[97],"indispensable":[99],"critical":[101],"perception":[102,188],"such":[104,160],"multi-view":[106],"3D":[107,171],"fusion.":[108],"To":[109,142],"address":[110],"these":[111],"limitations,":[112],"we":[113,151],"propose":[114],"Deformba,":[115,150],"context":[117],"adaptive":[118],"method":[119],"dynamically":[121],"augments":[122],"spatial":[124],"structural":[125],"while":[127],"maintaining":[128],"linear":[130],"SSMs.":[133],"Deformba":[134,181],"also":[135],"allows":[136],"multi-modal":[137],"like":[139,174],"cross":[140],"attention.":[141],"demonstrate":[143],"effectiveness":[145],"general":[147,156],"applicability":[148],"test":[152],"its":[153],"performance":[154,184],"2D":[157],"classification,":[163],"object":[164],"detection,":[165],"segmentation,":[167],"well":[169],"BEV":[175],"perception.":[176],"Extensive":[177],"experiments":[178],"show":[179],"achieves":[182],"strong":[183],"across":[185],"various":[186],"visual":[187],"benchmarks.":[189]},"counts_by_year":[],"updated_date":"2026-07-01T06:00:48.157686","created_date":"2026-05-22T00:00:00"}
