{"id":"https://openalex.org/W4403792071","doi":"https://doi.org/10.1145/3664647.3680832","title":"Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks","display_name":"Towards Low-latency Event-based Visual Recognition with Hybrid Step-wise Distillation Spiking Neural Networks","publication_year":2024,"publication_date":"2024-10-26","ids":{"openalex":"https://openalex.org/W4403792071","doi":"https://doi.org/10.1145/3664647.3680832"},"language":"en","primary_location":{"id":"doi:10.1145/3664647.3680832","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","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/A5064738683","display_name":"Xian Zhong","orcid":"https://orcid.org/0000-0002-5242-0467"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Xian Zhong","raw_affiliation_strings":["Wuhan University of Technology & Nanyang Technological University, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0002-5242-0467","affiliations":[{"raw_affiliation_string":"Wuhan University of Technology & Nanyang Technological University, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103782210","display_name":"Shengwang Hu","orcid":"https://orcid.org/0009-0003-7295-2596"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shengwang Hu","raw_affiliation_strings":["Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0009-0003-7295-2596","affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101564555","display_name":"Wenxuan Liu","orcid":"https://orcid.org/0000-0002-4417-6628"},"institutions":[{"id":"https://openalex.org/I196699116","display_name":"Wuhan University of Technology","ror":"https://ror.org/03fe7t173","country_code":"CN","type":"education","lineage":["https://openalex.org/I196699116"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxuan Liu","raw_affiliation_strings":["Wuhan University of Technology, Wuhan, Hubei, China"],"raw_orcid":"https://orcid.org/0000-0002-4417-6628","affiliations":[{"raw_affiliation_string":"Wuhan University of Technology, Wuhan, Hubei, China","institution_ids":["https://openalex.org/I196699116"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101949151","display_name":"Wenxin Huang","orcid":"https://orcid.org/0000-0001-8683-7327"},"institutions":[{"id":"https://openalex.org/I75900474","display_name":"Hubei University","ror":"https://ror.org/03a60m280","country_code":"CN","type":"education","lineage":["https://openalex.org/I75900474"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wenxin Huang","raw_affiliation_strings":["Hubei University, Wuhan, China"],"raw_orcid":"https://orcid.org/0000-0001-8683-7327","affiliations":[{"raw_affiliation_string":"Hubei University, Wuhan, China","institution_ids":["https://openalex.org/I75900474"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030879654","display_name":"Jianhao Ding","orcid":"https://orcid.org/0000-0001-5171-1898"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jianhao Ding","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0001-5171-1898","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103008727","display_name":"Zhaofei Yu","orcid":"https://orcid.org/0000-0003-0683-6936"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhaofei Yu","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-0683-6936","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5058066577","display_name":"Tiejun Huang","orcid":"https://orcid.org/0000-0002-4234-6099"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Tiejun Huang","raw_affiliation_strings":["Peking University, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0002-4234-6099","affiliations":[{"raw_affiliation_string":"Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"9828","last_page":"9836"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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"}},"topics":[{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":1.0,"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"}},{"id":"https://openalex.org/T11992","display_name":"CCD and CMOS Imaging Sensors","score":0.9972000122070312,"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"}},{"id":"https://openalex.org/T10581","display_name":"Neural dynamics and brain function","score":0.9941999912261963,"subfield":{"id":"https://openalex.org/subfields/2805","display_name":"Cognitive Neuroscience"},"field":{"id":"https://openalex.org/fields/28","display_name":"Neuroscience"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7719732522964478},{"id":"https://openalex.org/keywords/spiking-neural-network","display_name":"Spiking neural network","score":0.6591771841049194},{"id":"https://openalex.org/keywords/latency","display_name":"Latency (audio)","score":0.5851421356201172},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5652216076850891},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5390638113021851},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.4835607707500458},{"id":"https://openalex.org/keywords/distillation","display_name":"Distillation","score":0.45411327481269836},{"id":"https://openalex.org/keywords/deep-neural-networks","display_name":"Deep neural networks","score":0.4278988242149353},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.37698301672935486},{"id":"https://openalex.org/keywords/chemistry","display_name":"Chemistry","score":0.0757283866405487}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7719732522964478},{"id":"https://openalex.org/C11731999","wikidata":"https://www.wikidata.org/wiki/Q9067355","display_name":"Spiking neural network","level":3,"score":0.6591771841049194},{"id":"https://openalex.org/C82876162","wikidata":"https://www.wikidata.org/wiki/Q17096504","display_name":"Latency (audio)","level":2,"score":0.5851421356201172},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5652216076850891},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5390638113021851},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.4835607707500458},{"id":"https://openalex.org/C204030448","wikidata":"https://www.wikidata.org/wiki/Q101017","display_name":"Distillation","level":2,"score":0.45411327481269836},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.4278988242149353},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.37698301672935486},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0757283866405487},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.0},{"id":"https://openalex.org/C178790620","wikidata":"https://www.wikidata.org/wiki/Q11351","display_name":"Organic chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3664647.3680832","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3664647.3680832","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 32nd ACM International Conference on Multimedia","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":30,"referenced_works":["https://openalex.org/W1994616650","https://openalex.org/W2006370340","https://openalex.org/W2775079417","https://openalex.org/W2962804204","https://openalex.org/W2974328520","https://openalex.org/W2990793844","https://openalex.org/W3034368386","https://openalex.org/W3040838455","https://openalex.org/W3093471076","https://openalex.org/W3102040318","https://openalex.org/W3102750118","https://openalex.org/W3138154797","https://openalex.org/W3157350647","https://openalex.org/W3162489473","https://openalex.org/W3186268528","https://openalex.org/W3208010266","https://openalex.org/W4221155907","https://openalex.org/W4221157818","https://openalex.org/W4367043296","https://openalex.org/W4384831993","https://openalex.org/W4386071675","https://openalex.org/W4386763804","https://openalex.org/W4387409844","https://openalex.org/W4390872075","https://openalex.org/W4390872397","https://openalex.org/W4392796587","https://openalex.org/W4393157125","https://openalex.org/W4393158836","https://openalex.org/W4394698802","https://openalex.org/W6863467833"],"related_works":["https://openalex.org/W3126544799","https://openalex.org/W3104333581","https://openalex.org/W2542565870","https://openalex.org/W3111828357","https://openalex.org/W3018398156","https://openalex.org/W2920832517","https://openalex.org/W4388827557","https://openalex.org/W4387877594","https://openalex.org/W3153981999","https://openalex.org/W4225894772"],"abstract_inverted_index":{"Spiking":[0],"neural":[1],"networks":[2],"(SNNs)":[3],"have":[4],"garnered":[5],"significant":[6],"attention":[7],"for":[8,30,57],"their":[9],"low":[10,133],"power":[11],"consumption":[12],"and":[13,23,40,82],"high":[14],"biological":[15],"interpretability.":[16],"Their":[17],"rich":[18],"spatio-temporal":[19],"information":[20],"processing":[21],"capability":[22],"event-driven":[24],"nature":[25],"make":[26],"them":[27],"ideally":[28],"well-suited":[29],"neuromorphic":[31,58,173],"datasets.":[32,45],"However,":[33],"current":[34],"SNNs":[35,116,155],"struggle":[36],"to":[37,60,96,108,123],"balance":[38],"accuracy":[39],"latency":[41],"in":[42,65,150,169],"classifying":[43],"these":[44],"In":[46],"this":[47,138],"paper,":[48],"we":[49,140],"propose":[50],"Hybrid":[51],"Step-wise":[52,142],"Distillation":[53,144],"(HSD)":[54],"method,":[55],"tailored":[56],"datasets,":[59,174],"mitigate":[61],"the":[62,74,77,83,93,105,112,151],"notable":[63],"decline":[64],"performance":[66,168],"at":[67,131,156,176],"lower":[68,177],"time":[69,84,119,125,134,158,178],"steps.":[70,135,179],"Our":[71,180],"work":[72],"disentangles":[73],"dependency":[75],"between":[76],"number":[78],"of":[79,86,115,154],"event":[80,90,102],"frames":[81,91,103],"steps":[85,120],"SNNs,":[87],"utilizing":[88],"more":[89],"during":[92,104],"training":[94],"stage":[95,107],"improve":[97],"performance,":[98],"while":[99],"using":[100],"fewer":[101],"inference":[106],"reduce":[109],"latency.":[110],"Nevertheless,":[111],"average":[113],"output":[114,152],"across":[117],"all":[118],"is":[121],"susceptible":[122],"individual":[124],"step":[126],"with":[127],"abnormal":[128],"outputs,":[129],"particularly":[130],"extremely":[132],"To":[136],"tackle":[137],"issue,":[139],"implement":[141],"Knowledge":[143],"(SKD)":[145],"module":[146],"that":[147,163],"considers":[148],"variations":[149],"distribution":[153],"each":[157],"step.":[159],"Empirical":[160],"evidence":[161],"demonstrates":[162],"our":[164],"method":[165],"yields":[166],"competitive":[167],"classification":[170],"tasks":[171],"on":[172],"especially":[175],"code":[181],"will":[182],"be":[183],"available":[184],"at:":[185],"https://github.com/hsw0929/HSD.":[186]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":2}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}