{"id":"https://openalex.org/W4416251778","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228819","title":"Deep Spiking Neural Network with Adaptive Temporal Feature Fusion for Energy-efficient Event-based Person Re-Identification","display_name":"Deep Spiking Neural Network with Adaptive Temporal Feature Fusion for Energy-efficient Event-based Person Re-Identification","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416251778","doi":"https://doi.org/10.1109/ijcnn64981.2025.11228819"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11228819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},"type":"conference-paper","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/A5114151316","display_name":"Qingfeng Shi","orcid":"https://orcid.org/0009-0000-8480-9314"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qingfeng Shi","raw_affiliation_strings":["Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5025899376","display_name":"Jiaqiang Jiang","orcid":"https://orcid.org/0009-0007-2553-9896"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiaqiang Jiang","raw_affiliation_strings":["Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5111500162","display_name":"Huajin Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I168879160","display_name":"Zhejiang University of Science and Technology","ror":"https://ror.org/05mx0wr29","country_code":"CN","type":"education","lineage":["https://openalex.org/I168879160"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Huajin Tang","raw_affiliation_strings":["Zhejiang University,College of Computer Science and Technology,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I168879160"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046836420","display_name":"Rui Yan","orcid":"https://orcid.org/0000-0003-0048-3092"},"institutions":[{"id":"https://openalex.org/I55712492","display_name":"Zhejiang University of Technology","ror":"https://ror.org/02djqfd08","country_code":"CN","type":"education","lineage":["https://openalex.org/I55712492"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rui Yan","raw_affiliation_strings":["Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Zhejiang University of Technology,College of Computer Science and Technology,Hangzhou,China","institution_ids":["https://openalex.org/I55712492"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"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":"1","last_page":"8"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10331","display_name":"Video Surveillance and Tracking Methods","score":0.23199999332427979,"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":0.23199999332427979,"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/T12740","display_name":"Gait Recognition and Analysis","score":0.18070000410079956,"subfield":{"id":"https://openalex.org/subfields/2204","display_name":"Biomedical Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10036","display_name":"Advanced Neural Network Applications","score":0.1469999998807907,"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/discriminative-model","display_name":"Discriminative model","score":0.7476000189781189},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.5794000029563904},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.536899983882904},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.5338000059127808},{"id":"https://openalex.org/keywords/neural-coding","display_name":"Neural coding","score":0.4659000039100647},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.45840001106262207},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.44339999556541443},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.42260000109672546},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.41359999775886536},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4036000072956085}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8345000147819519},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.7476000189781189},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7247999906539917},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.5794000029563904},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.536899983882904},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.5338000059127808},{"id":"https://openalex.org/C77637269","wikidata":"https://www.wikidata.org/wiki/Q7002051","display_name":"Neural coding","level":2,"score":0.4659000039100647},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.45840001106262207},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.44339999556541443},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.42260000109672546},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.41359999775886536},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4036000072956085},{"id":"https://openalex.org/C33954974","wikidata":"https://www.wikidata.org/wiki/Q486494","display_name":"Sensor fusion","level":2,"score":0.3817000091075897},{"id":"https://openalex.org/C59404180","wikidata":"https://www.wikidata.org/wiki/Q17013334","display_name":"Feature learning","level":2,"score":0.3765999972820282},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.3596999943256378},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.35920000076293945},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.3547999858856201},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.32910001277923584},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.32760000228881836},{"id":"https://openalex.org/C165064840","wikidata":"https://www.wikidata.org/wiki/Q1321061","display_name":"Matching (statistics)","level":2,"score":0.32510000467300415},{"id":"https://openalex.org/C63479239","wikidata":"https://www.wikidata.org/wiki/Q7353546","display_name":"Robustness (evolution)","level":3,"score":0.3100000023841858},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.2883000075817108},{"id":"https://openalex.org/C158525013","wikidata":"https://www.wikidata.org/wiki/Q2593739","display_name":"Fusion","level":2,"score":0.28760001063346863},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.2867000102996826},{"id":"https://openalex.org/C2983787585","wikidata":"https://www.wikidata.org/wiki/Q93586","display_name":"Feature matching","level":3,"score":0.2815999984741211},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.28049999475479126},{"id":"https://openalex.org/C186370098","wikidata":"https://www.wikidata.org/wiki/Q442787","display_name":"Energy (signal processing)","level":2,"score":0.2750000059604645},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.26660001277923584},{"id":"https://openalex.org/C2988886741","wikidata":"https://www.wikidata.org/wiki/Q25304494","display_name":"Dictionary learning","level":3,"score":0.26429998874664307},{"id":"https://openalex.org/C116409475","wikidata":"https://www.wikidata.org/wiki/Q1385056","display_name":"External Data Representation","level":2,"score":0.26249998807907104},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.26089999079704285}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11228819","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11228819","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320335777","display_name":"National Key Research and Development Program of China","ror":null}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1604973310","https://openalex.org/W1999085092","https://openalex.org/W2132870234","https://openalex.org/W2621826044","https://openalex.org/W2783525259","https://openalex.org/W2796402180","https://openalex.org/W2892077605","https://openalex.org/W2904275768","https://openalex.org/W2963736028","https://openalex.org/W2966081953","https://openalex.org/W2966513546","https://openalex.org/W2984145721","https://openalex.org/W2986451890","https://openalex.org/W2990928867","https://openalex.org/W3034494316","https://openalex.org/W3040838455","https://openalex.org/W3092917503","https://openalex.org/W3102040318","https://openalex.org/W3102750118","https://openalex.org/W3173635859","https://openalex.org/W3176633985","https://openalex.org/W3187816944","https://openalex.org/W3194940645","https://openalex.org/W3195939161","https://openalex.org/W4213277438","https://openalex.org/W4281385234","https://openalex.org/W4386065939","https://openalex.org/W4390873006","https://openalex.org/W4391661519","https://openalex.org/W4404690083"],"related_works":[],"abstract_inverted_index":{"Video":[0],"surveillance":[1],"is":[2],"widely":[3],"used":[4],"in":[5,22,44,89,100,166],"various":[6],"public":[7],"spaces,":[8],"and":[9,47,64,80,120,162,196],"person":[10,136,153],"re-identification":[11],"(ReId)":[12],"based":[13,138,179],"on":[14,139,180,191],"video":[15],"frames":[16],"has":[17],"become":[18],"a":[19,94],"research":[20],"hotspot":[21],"the":[23,49,129,147],"field":[24],"of":[25,51,131],"computer":[26],"vision.":[27],"However,":[28],"most":[29],"video-based":[30],"methods":[31,59],"struggle":[32],"with":[33],"issues":[34,157],"such":[35,118,158],"as":[36,75,159],"poor":[37,163],"lighting":[38,98],"or":[39],"motion":[40],"blur,":[41],"which":[42,107],"result":[43],"blurry":[45,160],"textures":[46],"hinder":[48],"extraction":[50],"discriminative":[52],"features":[53],"for":[54,135,146,152],"specific":[55,101],"identities.":[56],"Additionally,":[57],"frame-based":[58],"may":[60],"introduce":[61],"privacy":[62],"concerns":[63],"suffer":[65,155],"from":[66,156],"redundant":[67],"storage":[68],"between":[69],"frames.":[70],"In":[71,124],"contrast,":[72],"bio-inspired":[73],"sensors\u2014such":[74],"event":[76,144],"cameras\u2014have":[77],"asynchronous":[78,119],"properties":[79],"higher":[81],"temporal":[82,174],"resolution.":[83],"They":[84],"record":[85],"events":[86],"when":[87],"changes":[88],"light":[90],"intensity":[91],"occur,":[92],"offering":[93],"better":[95],"response":[96],"to":[97,116,183,199],"variations":[99],"scenes.":[102],"Spiking":[103],"Neural":[104],"Networks":[105],"(SNNs),":[106],"transmit":[108],"information":[109],"through":[110],"sparse":[111,121],"spikes,":[112],"are":[113],"naturally":[114],"suited":[115],"process":[117],"event-stream":[122,140],"inputs.":[123],"this":[125],"work,":[126],"we":[127,170],"explore":[128],"possibility":[130],"using":[132],"only":[133],"SNN":[134],"ReId":[137,154],"data":[141],"generated":[142],"by":[143,211],"cameras":[145],"first":[148],"time.":[149],"While":[150],"SNNs":[151],"matching":[161],"feature":[164,168,175],"distinction":[165],"spike-based":[167],"matching,":[169],"propose":[171],"an":[172],"adaptive":[173],"representation":[176],"(ATFR)":[177],"method":[178,190],"membrane":[181],"potential":[182],"address":[184],"these":[185],"issues.":[186],"We":[187],"evaluate":[188],"our":[189,202],"two":[192],"event-based":[193],"datasets":[194],"(Event-ReId":[195],"Event-PRID-2011).":[197],"Compared":[198],"existing":[200],"methods,":[201],"model":[203],"achieves":[204],"competitive":[205],"performance":[206],"while":[207],"improving":[208],"energy":[209],"efficiency":[210],"at":[212],"least":[213],"6":[214],"times.":[215]},"counts_by_year":[],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-11-14T00:00:00"}