{"id":"https://openalex.org/W4416250252","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227637","title":"SaENeRF: Suppressing Artifacts in Event-based Neural Radiance Fields","display_name":"SaENeRF: Suppressing Artifacts in Event-based Neural Radiance Fields","publication_year":2025,"publication_date":"2025-06-30","ids":{"openalex":"https://openalex.org/W4416250252","doi":"https://doi.org/10.1109/ijcnn64981.2025.11227637"},"language":null,"primary_location":{"id":"doi:10.1109/ijcnn64981.2025.11227637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227637","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/A5051444274","display_name":"Yuanjian Wang","orcid":"https://orcid.org/0000-0003-0831-4293"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yuanjian Wang","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109538183","display_name":"Yufei Deng","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yufei Deng","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084417688","display_name":"Rong Xiao","orcid":"https://orcid.org/0000-0002-6408-9724"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Rong Xiao","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5024075091","display_name":"Jiahao Fan","orcid":"https://orcid.org/0000-0002-0818-8533"},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahao Fan","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109717488","display_name":"Chenwei Tang","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenwei Tang","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082236554","display_name":"Xiong Deng","orcid":"https://orcid.org/0000-0002-5207-471X"},"institutions":[{"id":"https://openalex.org/I108468826","display_name":"Stevens Institute of Technology","ror":"https://ror.org/02z43xh36","country_code":"US","type":"education","lineage":["https://openalex.org/I108468826"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Deng Xiong","raw_affiliation_strings":["Stevens Institute of Technology,Hoboken,USA"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Stevens Institute of Technology,Hoboken,USA","institution_ids":["https://openalex.org/I108468826"]}]},{"author_position":"last","author":{"id":null,"display_name":"Jiancheng Lv","orcid":null},"institutions":[{"id":"https://openalex.org/I24185976","display_name":"Sichuan University","ror":"https://ror.org/011ashp19","country_code":"CN","type":"education","lineage":["https://openalex.org/I24185976"]},{"id":"https://openalex.org/I4210125143","display_name":"Chengdu University","ror":"https://ror.org/034z67559","country_code":"CN","type":"education","lineage":["https://openalex.org/I4210125143"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiancheng Lv","raw_affiliation_strings":["Sichuan University,College of Computer Science,Chengdu,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Sichuan University,College of Computer Science,Chengdu,China","institution_ids":["https://openalex.org/I24185976","https://openalex.org/I4210125143"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9842000007629395,"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":0.9842000007629395,"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/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.005400000140070915,"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/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.0031999999191612005,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/radiance","display_name":"Radiance","score":0.6452000141143799},{"id":"https://openalex.org/keywords/brightness","display_name":"Brightness","score":0.6198999881744385},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5353999733924866},{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.45829999446868896},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.45820000767707825},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.4115000069141388},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.4097999930381775},{"id":"https://openalex.org/keywords/iterative-reconstruction","display_name":"Iterative reconstruction","score":0.39399999380111694},{"id":"https://openalex.org/keywords/fidelity","display_name":"Fidelity","score":0.3700999915599823}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7469000220298767},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6966000199317932},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6901000142097473},{"id":"https://openalex.org/C23690007","wikidata":"https://www.wikidata.org/wiki/Q1411145","display_name":"Radiance","level":2,"score":0.6452000141143799},{"id":"https://openalex.org/C125245961","wikidata":"https://www.wikidata.org/wiki/Q221656","display_name":"Brightness","level":2,"score":0.6198999881744385},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5353999733924866},{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.45829999446868896},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.45820000767707825},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.4115000069141388},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.4097999930381775},{"id":"https://openalex.org/C141379421","wikidata":"https://www.wikidata.org/wiki/Q6094427","display_name":"Iterative reconstruction","level":2,"score":0.39399999380111694},{"id":"https://openalex.org/C2776459999","wikidata":"https://www.wikidata.org/wiki/Q2119376","display_name":"Fidelity","level":2,"score":0.3700999915599823},{"id":"https://openalex.org/C73313986","wikidata":"https://www.wikidata.org/wiki/Q355386","display_name":"Luminance","level":2,"score":0.36719998717308044},{"id":"https://openalex.org/C2776135515","wikidata":"https://www.wikidata.org/wiki/Q17143721","display_name":"Regularization (linguistics)","level":2,"score":0.33379998803138733},{"id":"https://openalex.org/C39927690","wikidata":"https://www.wikidata.org/wiki/Q11197","display_name":"Logarithm","level":2,"score":0.3269999921321869},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.32330000400543213},{"id":"https://openalex.org/C113364801","wikidata":"https://www.wikidata.org/wiki/Q26674","display_name":"High fidelity","level":2,"score":0.3093999922275543},{"id":"https://openalex.org/C2775853353","wikidata":"https://www.wikidata.org/wiki/Q5416724","display_name":"Event reconstruction","level":3,"score":0.30550000071525574},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.29989999532699585},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.29660001397132874},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.28450000286102295},{"id":"https://openalex.org/C3020368824","wikidata":"https://www.wikidata.org/wiki/Q6546192","display_name":"Light intensity","level":2,"score":0.27230000495910645},{"id":"https://openalex.org/C2776760102","wikidata":"https://www.wikidata.org/wiki/Q5139990","display_name":"Code (set theory)","level":3,"score":0.257999986410141},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2563000023365021}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn64981.2025.11227637","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn64981.2025.11227637","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":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":35,"referenced_works":["https://openalex.org/W2118223742","https://openalex.org/W2122572959","https://openalex.org/W2133665775","https://openalex.org/W2519559998","https://openalex.org/W2530906228","https://openalex.org/W2783185291","https://openalex.org/W2885478207","https://openalex.org/W2962785568","https://openalex.org/W2998281665","https://openalex.org/W3040838455","https://openalex.org/W3109585842","https://openalex.org/W3139658937","https://openalex.org/W3144939529","https://openalex.org/W3189852228","https://openalex.org/W4205106798","https://openalex.org/W4221145923","https://openalex.org/W4221151978","https://openalex.org/W4226017061","https://openalex.org/W4237648096","https://openalex.org/W4283800840","https://openalex.org/W4312400353","https://openalex.org/W4318586184","https://openalex.org/W4319299752","https://openalex.org/W4378450585","https://openalex.org/W4385318467","https://openalex.org/W4386076266","https://openalex.org/W4390871880","https://openalex.org/W4390873524","https://openalex.org/W4390873806","https://openalex.org/W4394596432","https://openalex.org/W4401415384","https://openalex.org/W4402698362","https://openalex.org/W4402753362","https://openalex.org/W4402754283","https://openalex.org/W4402979620"],"related_works":[],"abstract_inverted_index":{"Event":[0],"cameras":[1],"are":[2],"neuromorphic":[3],"vision":[4],"sensors":[5],"that":[6,95,179],"asynchronously":[7],"capture":[8],"changes":[9,148],"in":[10,74,144],"logarithmic":[11],"brightness":[12],"changes,":[13],"offering":[14],"significant":[15],"advantages":[16],"such":[17],"as":[18],"low":[19,21,24],"latency,":[20],"power":[22],"consumption,":[23],"bandwidth,":[25],"and":[26,42,77,99,103,127,154,175,185],"high":[27],"dynamic":[28],"range.":[29],"While":[30],"these":[31,62,86],"characteristics":[32],"make":[33],"them":[34],"ideal":[35],"for":[36,130],"high-speed":[37],"scenarios,":[38],"reconstructing":[39],"geometrically":[40],"consistent":[41],"photometrically":[43],"accurate":[44],"3D":[45],"representations":[46],"from":[47,66,111],"event":[48,82,112,123,152],"data":[49],"remains":[50],"fundamentally":[51],"challenging.":[52],"Current":[53],"event-based":[54],"Neural":[55],"Radiance":[56],"Fields":[57],"(NeRF)":[58],"methods":[59],"partially":[60],"address":[61],"challenges":[63],"but":[64],"suffer":[65],"persistent":[67],"artifacts":[68,98,143,184],"caused":[69],"by":[70],"aggressive":[71],"network":[72],"learning":[73,129],"early":[75],"stages":[76],"the":[78,151,157,166,170],"inherent":[79],"noise":[80],"of":[81,107,161,169],"cameras.":[83],"To":[84],"overcome":[85],"limitations,":[87],"we":[88,135],"present":[89],"SaENeRF,":[90],"a":[91],"novel":[92],"self-supervised":[93],"framework":[94],"effectively":[96],"suppresses":[97],"enables":[100],"3D-consistent,":[101],"dense,":[102],"photorealistic":[104],"NeRF":[105],"reconstruction":[106,188],"static":[108],"scenes":[109],"solely":[110],"streams.":[113],"Our":[114],"approach":[115],"normalizes":[116],"predicted":[117],"radiance":[118],"variations":[119],"based":[120],"on":[121],"accumulated":[122],"polarities,":[124],"facilitating":[125],"progressive":[126],"rapid":[128],"scene":[131],"representation":[132],"construction.":[133],"Additionally,":[134],"introduce":[136],"regularization":[137],"losses":[138],"specifically":[139],"designed":[140],"to":[141,191],"suppress":[142],"regions":[145],"where":[146],"photometric":[147],"fall":[149],"below":[150],"threshold":[153],"simultaneously":[155],"enhance":[156],"light":[158],"intensity":[159],"difference":[160],"non-zero":[162],"events,":[163],"thereby":[164],"improving":[165],"visual":[167],"fidelity":[168],"reconstructed":[171],"scene.":[172],"Extensive":[173],"qualitative":[174],"quantitative":[176],"experiments":[177],"demonstrate":[178],"our":[180],"method":[181],"significantly":[182],"reduces":[183],"achieves":[186],"superior":[187],"quality":[189],"compared":[190],"existing":[192],"methods.":[193],"The":[194],"code":[195],"is":[196],"available":[197],"at":[198],"https://github.com/Mr-firework/SaENeRF.":[199]},"counts_by_year":[],"updated_date":"2026-07-22T07:51:19.307946","created_date":"2025-11-14T00:00:00"}
