{"id":"https://openalex.org/W7167285590","doi":"https://doi.org/10.1117/1.jei.35.4.043002","title":"TSR-SSM: temporal scale-robust state-space models for efficient event optical flow","display_name":"TSR-SSM: temporal scale-robust state-space models for efficient event optical flow","publication_year":2026,"publication_date":"2026-07-04","ids":{"openalex":"https://openalex.org/W7167285590","doi":"https://doi.org/10.1117/1.jei.35.4.043002"},"language":null,"primary_location":{"id":"doi:10.1117/1.jei.35.4.043002","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.jei.35.4.043002","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-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/A5048371289","display_name":"Jianming Wang","orcid":"https://orcid.org/0000-0003-2685-4437"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]},{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianming Wang","raw_affiliation_strings":["Tiangong University, School of Computer Science and Technology, Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0003-2685-4437","affiliations":[{"raw_affiliation_string":"Tiangong University, School of Computer Science and Technology, Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems, Tianjin, China","institution_ids":["https://openalex.org/I136765683","https://openalex.org/I198091727"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5020541310","display_name":"Yukuan Sun","orcid":"https://orcid.org/0000-0002-8886-6137"},"institutions":[{"id":"https://openalex.org/I136765683","display_name":"Tianjin University of Technology","ror":"https://ror.org/00zbe0w13","country_code":"CN","type":"education","lineage":["https://openalex.org/I136765683"]},{"id":"https://openalex.org/I198091727","display_name":"Tiangong University","ror":"https://ror.org/00xsr9m91","country_code":"CN","type":"education","lineage":["https://openalex.org/I198091727"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yukuan Sun","raw_affiliation_strings":["Tiangong University, Center for Engineering Internship and Training, Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems, Tianjin, China"],"raw_orcid":"https://orcid.org/0000-0002-8886-6137","affiliations":[{"raw_affiliation_string":"Tiangong University, Center for Engineering Internship and Training, Tianjin Key Laboratory of Autonomous Intelligence Technology and Systems, Tianjin, China","institution_ids":["https://openalex.org/I136765683","https://openalex.org/I198091727"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.838689,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"35","issue":"04","first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10531","display_name":"Advanced Vision and Imaging","score":0.1793999969959259,"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/T10531","display_name":"Advanced Vision and Imaging","score":0.1793999969959259,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.1615000069141388,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.11190000176429749,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic 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/sampling","display_name":"Sampling (signal processing)","score":0.6378999948501587},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5680000185966492},{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.5216000080108643},{"id":"https://openalex.org/keywords/stability","display_name":"Stability (learning theory)","score":0.5126000046730042},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.47839999198913574},{"id":"https://openalex.org/keywords/temporal-resolution","display_name":"Temporal resolution","score":0.46480000019073486},{"id":"https://openalex.org/keywords/reduction","display_name":"Reduction (mathematics)","score":0.45969998836517334},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.42980000376701355},{"id":"https://openalex.org/keywords/temporal-database","display_name":"Temporal database","score":0.38960000872612}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7204999923706055},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.6378999948501587},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5680000185966492},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.5216000080108643},{"id":"https://openalex.org/C112972136","wikidata":"https://www.wikidata.org/wiki/Q7595718","display_name":"Stability (learning theory)","level":2,"score":0.5126000046730042},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.47839999198913574},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.46480000019073486},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.45969998836517334},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.44699999690055847},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42980000376701355},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.4174000024795532},{"id":"https://openalex.org/C77277458","wikidata":"https://www.wikidata.org/wiki/Q1969246","display_name":"Temporal database","level":2,"score":0.38960000872612},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.376800000667572},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.36559998989105225},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.362199991941452},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.34860000014305115},{"id":"https://openalex.org/C67186912","wikidata":"https://www.wikidata.org/wiki/Q367664","display_name":"Data modeling","level":2,"score":0.3384000062942505},{"id":"https://openalex.org/C88871306","wikidata":"https://www.wikidata.org/wiki/Q7208287","display_name":"Point process","level":2,"score":0.3314000070095062},{"id":"https://openalex.org/C2778067643","wikidata":"https://www.wikidata.org/wiki/Q166507","display_name":"Interval (graph theory)","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C72434380","wikidata":"https://www.wikidata.org/wiki/Q230930","display_name":"State space","level":2,"score":0.296999990940094},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28940001130104065},{"id":"https://openalex.org/C48103436","wikidata":"https://www.wikidata.org/wiki/Q599031","display_name":"State (computer science)","level":2,"score":0.2816999852657318},{"id":"https://openalex.org/C28719098","wikidata":"https://www.wikidata.org/wiki/Q44946","display_name":"Point (geometry)","level":2,"score":0.28110000491142273},{"id":"https://openalex.org/C2777489503","wikidata":"https://www.wikidata.org/wiki/Q7698936","display_name":"Temporal scales","level":2,"score":0.2791000008583069},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.25940001010894775},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.25850000977516174},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.25690001249313354},{"id":"https://openalex.org/C52740198","wikidata":"https://www.wikidata.org/wiki/Q1539564","display_name":"Importance sampling","level":3,"score":0.25589999556541443},{"id":"https://openalex.org/C167928553","wikidata":"https://www.wikidata.org/wiki/Q1376021","display_name":"Estimation theory","level":2,"score":0.2542000114917755},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.2508000135421753}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1117/1.jei.35.4.043002","is_oa":false,"landing_page_url":"https://doi.org/10.1117/1.jei.35.4.043002","pdf_url":null,"source":{"id":"https://openalex.org/S158511090","display_name":"Journal of Electronic Imaging","issn_l":"1017-9909","issn":["1017-9909","1560-229X"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310315543","host_organization_name":"SPIE","host_organization_lineage":["https://openalex.org/P4310315543"],"host_organization_lineage_names":["SPIE"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Journal of Electronic Imaging","raw_type":"journal-article"}],"best_oa_location":null,"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":{"Event-based":[0],"optical-flow":[1,73,176],"estimation":[2,177],"remains":[3],"challenging":[4],"across":[5,178],"different":[6],"fixed-frequency":[7],"sampling,":[8],"particularly":[9],"under":[10,94,145,152],"low-frequency":[11,153],"conditions":[12,154],"where":[13],"observations":[14],"are":[15,20],"sparse":[16],"and":[17,30,56,127,148,173],"motion":[18],"displacements":[19],"large.":[21],"Conventional":[22],"methods":[23],"based":[24],"on":[25,124,163],"convolutional":[26],"neural":[27,32],"networks":[28,33],"(CNNs)":[29],"recurrent":[31],"(RNNs)":[34],"update":[35],"their":[36],"states":[37],"at":[38,160],"fixed":[39,87,96],"discrete-time":[40],"steps,":[41],"ignoring":[42],"the":[43,77,82,125],"actual":[44],"temporal":[45,54,67,83,92,180],"intervals":[46],"between":[47],"events,":[48],"which":[49],"can":[50],"lead":[51],"to":[52,81],"inconsistent":[53],"modeling":[55,93,111],"reduced":[57],"accuracy.":[58],"To":[59],"address":[60],"these":[61],"challenges,":[62],"we":[63,101],"propose":[64],"TSR-SSM,":[65],"a":[66,138,149],"scale-robust":[68],"state-space":[69,110],"model":[70],"for":[71],"event-based":[72,175],"estimation.":[74],"TSR-SSM":[75,132,169],"discretizes":[76],"state":[78],"space":[79],"according":[80],"interval":[84],"of":[85],"each":[86,95],"sampling":[88,97,147],"setting,":[89],"enabling":[90],"consistent":[91],"setting.":[98],"In":[99],"addition,":[100],"design":[102],"an":[103],"SSM-enhanced":[104],"cascaded":[105],"decoder":[106],"that":[107,131,168],"integrates":[108],"spatial":[109,117],"with":[112],"stability":[113],"regularization,":[114],"capturing":[115],"long-range":[116],"dependencies":[118],"while":[119,155],"suppressing":[120],"high-frequency":[121],"noise.":[122],"Experiments":[123],"HREM":[126],"DSEC":[128],"datasets":[129],"show":[130],"consistently":[133],"outperforms":[134],"prior":[135],"methods,":[136],"achieving":[137],"4.2%":[139],"reduction":[140,151],"in":[141],"average":[142],"endpoint":[143],"error":[144],"standard":[146],"9.7%":[150],"maintaining":[156],"real-time":[157],"inference":[158],"speed":[159],"37.46":[161],"FPS":[162],"DSEC.":[164],"These":[165],"results":[166],"demonstrate":[167],"enables":[170],"accurate,":[171],"robust,":[172],"efficient":[174],"diverse":[179],"scales.":[181]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2026-07-04T00:00:00"}
