{"id":"https://openalex.org/W7169666071","doi":"https://doi.org/10.1007/978-981-92-3520-9_43","title":"MT-Filter: A Segment-Wise Spatio-Temporal Filter Inspired by Biological Vision","display_name":"MT-Filter: A Segment-Wise Spatio-Temporal Filter Inspired by Biological Vision","publication_year":2026,"publication_date":"2026-07-18","ids":{"openalex":"https://openalex.org/W7169666071","doi":"https://doi.org/10.1007/978-981-92-3520-9_43"},"language":"en","primary_location":{"id":"doi:10.1007/978-981-92-3520-9_43","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-981-92-3520-9_43","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-981-92-3520-9_43.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/978-981-92-3520-9_43.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5101508336","display_name":"Yuehua Chen","orcid":"https://orcid.org/0000-0002-4646-4017"},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210150840","display_name":"Ministry of Education","ror":"https://ror.org/04a3gjw65","country_code":"BD","type":"government","lineage":["https://openalex.org/I4210150840"]}],"countries":["BD","CN"],"is_corresponding":false,"raw_author_name":"Yuang Chen","raw_affiliation_strings":["Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China"],"raw_orcid":"https://orcid.org/0009-0001-5570-0034","affiliations":[{"raw_affiliation_string":"Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I4210150840"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5116870780","display_name":"Shuhan Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210150840","display_name":"Ministry of Education","ror":"https://ror.org/04a3gjw65","country_code":"BD","type":"government","lineage":["https://openalex.org/I4210150840"]}],"countries":["BD","CN"],"is_corresponding":false,"raw_author_name":"Shuhan Lv","raw_affiliation_strings":["Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I4210150840"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5141115101","display_name":"Fang Lin","orcid":null},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210150840","display_name":"Ministry of Education","ror":"https://ror.org/04a3gjw65","country_code":"BD","type":"government","lineage":["https://openalex.org/I4210150840"]}],"countries":["BD","CN"],"is_corresponding":false,"raw_author_name":"Fang Lin","raw_affiliation_strings":["Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I4210150840"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5141120623","display_name":"Yong Li","orcid":null},"institutions":[{"id":"https://openalex.org/I1327237609","display_name":"Ministry of Education of the People's Republic of China","ror":"https://ror.org/01mv9t934","country_code":"CN","type":"government","lineage":["https://openalex.org/I1327237609","https://openalex.org/I4210127390"]},{"id":"https://openalex.org/I4210150840","display_name":"Ministry of Education","ror":"https://ror.org/04a3gjw65","country_code":"BD","type":"government","lineage":["https://openalex.org/I4210150840"]}],"countries":["BD","CN"],"is_corresponding":true,"raw_author_name":"Yong Li","raw_affiliation_strings":["Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Key Laboratory of CTC&IE, Engineering University of PAP, Ministry of Education, Xi\u2019an, China","institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I4210150840"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5141120623"],"corresponding_institution_ids":["https://openalex.org/I1327237609","https://openalex.org/I4210150840"],"apc_list":{"value":5000,"currency":"EUR","value_usd":5392},"apc_paid":{"value":5000,"currency":"EUR","value_usd":5392},"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"539","last_page":"555"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/optical-flow","display_name":"Optical flow","score":0.6345999836921692},{"id":"https://openalex.org/keywords/rgb-color-model","display_name":"RGB color model","score":0.6144999861717224},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5819000005722046},{"id":"https://openalex.org/keywords/filter","display_name":"Filter (signal processing)","score":0.5612000226974487},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5281000137329102},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5180000066757202},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.44929999113082886},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.4311000108718872},{"id":"https://openalex.org/keywords/dimension","display_name":"Dimension (graph theory)","score":0.4259999990463257}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.873199999332428},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7196999788284302},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.6345999836921692},{"id":"https://openalex.org/C82990744","wikidata":"https://www.wikidata.org/wiki/Q166194","display_name":"RGB color model","level":2,"score":0.6144999861717224},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5819000005722046},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.5741000175476074},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.5612000226974487},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5281000137329102},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5180000066757202},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.44929999113082886},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.4311000108718872},{"id":"https://openalex.org/C33676613","wikidata":"https://www.wikidata.org/wiki/Q13415176","display_name":"Dimension (graph theory)","level":2,"score":0.4259999990463257},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.42480000853538513},{"id":"https://openalex.org/C196083921","wikidata":"https://www.wikidata.org/wiki/Q7915758","display_name":"Variance (accounting)","level":2,"score":0.4077000021934509},{"id":"https://openalex.org/C121475858","wikidata":"https://www.wikidata.org/wiki/Q2735911","display_name":"Spatial filter","level":2,"score":0.40540000796318054},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.38089999556541443},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.3488999903202057},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.310699999332428},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.30149999260902405},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.28870001435279846},{"id":"https://openalex.org/C159620131","wikidata":"https://www.wikidata.org/wiki/Q1938983","display_name":"Spatial analysis","level":2,"score":0.2842999994754791},{"id":"https://openalex.org/C179799912","wikidata":"https://www.wikidata.org/wiki/Q205084","display_name":"Computational complexity theory","level":2,"score":0.2831000089645386},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.27390000224113464},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.260699987411499},{"id":"https://openalex.org/C2780791683","wikidata":"https://www.wikidata.org/wiki/Q846785","display_name":"Action (physics)","level":2,"score":0.2554999887943268}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1007/978-981-92-3520-9_43","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-981-92-3520-9_43","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-981-92-3520-9_43.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"}],"best_oa_location":{"id":"doi:10.1007/978-981-92-3520-9_43","is_oa":true,"landing_page_url":"https://doi.org/10.1007/978-981-92-3520-9_43","pdf_url":"https://link.springer.com/content/pdf/10.1007/978-981-92-3520-9_43.pdf","source":{"id":"https://openalex.org/S106296714","display_name":"Lecture notes in computer science","issn_l":"0302-9743","issn":["0302-9743","1611-3349"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319900","host_organization_name":"Springer Science+Business Media","host_organization_lineage":["https://openalex.org/P4310319900","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Science+Business Media","Springer Nature"],"type":"book series"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Lecture Notes in Computer Science","raw_type":"book-chapter"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7508919323","display_name":null,"funder_award_id":"2025-SKJJ-A-007","funder_id":"https://openalex.org/F4320327557","funder_display_name":"National Office for Philosophy and Social Sciences"}],"funders":[{"id":"https://openalex.org/F4320327557","display_name":"National Office for Philosophy and Social Sciences","ror":"https://ror.org/04m0ms912"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7169666071.pdf","grobid_xml":"https://content.openalex.org/works/W7169666071.grobid-xml"},"referenced_works_count":26,"referenced_works":["https://openalex.org/W2080353936","https://openalex.org/W2560474170","https://openalex.org/W2899380829","https://openalex.org/W2963163009","https://openalex.org/W2963420686","https://openalex.org/W2963524571","https://openalex.org/W2994175816","https://openalex.org/W3020904378","https://openalex.org/W3185192194","https://openalex.org/W4224329855","https://openalex.org/W4292970355","https://openalex.org/W4293103202","https://openalex.org/W4320913003","https://openalex.org/W4323974789","https://openalex.org/W4324308744","https://openalex.org/W4406737423","https://openalex.org/W4408423489","https://openalex.org/W4409059714","https://openalex.org/W4409195463","https://openalex.org/W4410809609","https://openalex.org/W4411245233","https://openalex.org/W4411336874","https://openalex.org/W4411930718","https://openalex.org/W4412467832","https://openalex.org/W4412527736","https://openalex.org/W7133239857"],"related_works":[],"abstract_inverted_index":{"The":[0,156],"core":[1],"challenge":[2],"in":[3,8,48,99,134],"video":[4,122],"action":[5,132],"recognition":[6],"lies":[7],"efficiently":[9],"modeling":[10],"spatio-temporal":[11,63,97,164],"dynamics":[12],"and":[13,60,187,197],"precisely":[14],"capturing":[15],"discriminative":[16],"motion":[17,39,89],"cues,":[18],"whereas":[19],"existing":[20],"methods":[21],"often":[22],"rely":[23],"on":[24,130,143,185],"computationally":[25],"expensive":[26],"optical":[27],"flow":[28],"or":[29],"frame":[30],"differencing":[31],"with":[32,168],"severe":[33],"semantic":[34],"loss.":[35],"Inspired":[36],"by":[37],"the":[38,43,49,66,69,75,83,100,110,135,151,191],"perception":[40],"mechanism":[41,141],"of":[42,71,113,153,158],"Middle":[44],"Temporal":[45],"area":[46],"(MT/V5)":[47],"primate":[50],"visual":[51],"system,":[52],"this":[53],"paper":[54],"proposes":[55],"MT-Filter,":[56],"a":[57,103,138,161],"lightweight,":[58],"unsupervised,":[59],"plug-and-play":[61],"segment-wise":[62,104],"filter.":[64],"Under":[65],"zero-mean":[67],"assumption,":[68],"variance":[70,112],"feature":[72,114],"values":[73,115],"at":[74,116],"same":[76],"spatial":[77,101,118,126],"location":[78,119],"across":[79,120],"consecutive":[80,121],"frames":[81],"along":[82],"temporal":[84,111,136],"dimension":[85],"can":[86],"effectively":[87],"reflect":[88],"saliency.":[90],"MT-Filter":[91,176],"achieves":[92],"efficient":[93],"enhancement":[94],"through":[95],"decoupled":[96],"modeling:":[98],"dimension,":[102,137],"strategy":[105],"is":[106,146],"adopted":[107],"to":[108,128,148,181],"compute":[109],"each":[117,154],"frames,":[123],"generating":[124],"dynamic":[125],"weights":[127],"focus":[129],"genuine":[131],"regions;":[133],"frame-level":[139],"attention":[140],"based":[142],"Squeeze-and-Excitation":[144],"(SE)":[145],"introduced":[147],"adaptively":[149],"modulate":[150],"contribution":[152],"frame.":[155],"combination":[157],"both":[159],"forms":[160],"content-aware":[162],"three-dimensional":[163],"filter":[165],"that":[166,175],"operates":[167],"RGB":[169],"input":[170],"only.":[171],"Extensive":[172],"experiments":[173],"demonstrate":[174],"brings":[177],"consistent":[178],"performance":[179],"improvements":[180],"various":[182],"mainstream":[183],"architectures":[184],"UCF101":[186],"HMDB51":[188],"datasets.":[189],"Notably,":[190],"module":[192],"introduces":[193],"merely":[194],"10":[195],"parameters":[196],"1.2M":[198],"FLOPs,":[199],"adding":[200],"negligible":[201],"computational":[202],"overhead.":[203]},"counts_by_year":[],"updated_date":"2026-07-20T05:51:44.042241","created_date":"2026-07-19T00:00:00"}