{"id":"https://openalex.org/W4416125094","doi":"https://doi.org/10.1109/iccv51701.2025.00654","title":"Simultaneous Motion and Noise Estimation with Event Cameras","display_name":"Simultaneous Motion and Noise Estimation with Event Cameras","publication_year":2025,"publication_date":"2025-10-19","ids":{"openalex":"https://openalex.org/W4416125094","doi":"https://doi.org/10.1109/iccv51701.2025.00654"},"language":"en","primary_location":{"id":"doi:10.1109/iccv51701.2025.00654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2504.04029","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5040131269","display_name":"Shintaro Shiba","orcid":"https://orcid.org/0000-0002-1293-4113"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Shintaro Shiba","raw_affiliation_strings":["Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070908826","display_name":"Yoshimitsu Aoki","orcid":"https://orcid.org/0000-0001-7361-0027"},"institutions":[{"id":"https://openalex.org/I203951103","display_name":"Keio University","ror":"https://ror.org/02kn6nx58","country_code":"JP","type":"education","lineage":["https://openalex.org/I203951103"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Yoshimitsu Aoki","raw_affiliation_strings":["Keio University"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Keio University","institution_ids":["https://openalex.org/I203951103"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5068567652","display_name":"Guillermo Gallego","orcid":"https://orcid.org/0000-0002-2672-9241"},"institutions":[{"id":"https://openalex.org/I4577782","display_name":"Technische Universit\u00e4t Berlin","ror":"https://ror.org/03v4gjf40","country_code":"DE","type":"education","lineage":["https://openalex.org/I4577782"]}],"countries":["DE"],"is_corresponding":false,"raw_author_name":"Guillermo Gallego","raw_affiliation_strings":["Technische Universität Berlin,Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Technische Universität Berlin,Japan","institution_ids":["https://openalex.org/I4577782"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"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":0.286282,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"6959","last_page":"6969"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.9675999879837036,"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":0.9675999879837036,"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":0.006800000090152025,"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/T11181","display_name":"Advanced Data Storage Technologies","score":0.00559999980032444,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/noise-reduction","display_name":"Noise reduction","score":0.6671000123023987},{"id":"https://openalex.org/keywords/noise","display_name":"Noise (video)","score":0.6101999878883362},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5828999876976013},{"id":"https://openalex.org/keywords/motion-estimation","display_name":"Motion estimation","score":0.5412999987602234},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5390999913215637},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.534600019454956},{"id":"https://openalex.org/keywords/video-denoising","display_name":"Video denoising","score":0.421099990606308},{"id":"https://openalex.org/keywords/structure-from-motion","display_name":"Structure from motion","score":0.4099000096321106}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7627000212669373},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7414000034332275},{"id":"https://openalex.org/C163294075","wikidata":"https://www.wikidata.org/wiki/Q581861","display_name":"Noise reduction","level":2,"score":0.6671000123023987},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.656499981880188},{"id":"https://openalex.org/C99498987","wikidata":"https://www.wikidata.org/wiki/Q2210247","display_name":"Noise (video)","level":3,"score":0.6101999878883362},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5828999876976013},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.5412999987602234},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5390999913215637},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.534600019454956},{"id":"https://openalex.org/C30814859","wikidata":"https://www.wikidata.org/wiki/Q4119603","display_name":"Video denoising","level":5,"score":0.421099990606308},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.4099000096321106},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.335999995470047},{"id":"https://openalex.org/C174493125","wikidata":"https://www.wikidata.org/wiki/Q1073461","display_name":"Quarter-pixel motion","level":3,"score":0.3301999866962433},{"id":"https://openalex.org/C2776330181","wikidata":"https://www.wikidata.org/wiki/Q18358244","display_name":"Maximization","level":2,"score":0.3197000026702881},{"id":"https://openalex.org/C124774092","wikidata":"https://www.wikidata.org/wiki/Q6917782","display_name":"Motion field","level":3,"score":0.31540000438690186},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.3050999939441681},{"id":"https://openalex.org/C128840427","wikidata":"https://www.wikidata.org/wiki/Q1302174","display_name":"Motion compensation","level":2,"score":0.29170000553131104},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.28690001368522644},{"id":"https://openalex.org/C2776502983","wikidata":"https://www.wikidata.org/wiki/Q690182","display_name":"Contrast (vision)","level":2,"score":0.2782999873161316},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2694999873638153},{"id":"https://openalex.org/C29265498","wikidata":"https://www.wikidata.org/wiki/Q7047719","display_name":"Noise measurement","level":3,"score":0.2624000012874603},{"id":"https://openalex.org/C111335779","wikidata":"https://www.wikidata.org/wiki/Q3454686","display_name":"Reduction (mathematics)","level":2,"score":0.260699987411499},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.2606000006198883}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/iccv51701.2025.00654","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iccv51701.2025.00654","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2025 IEEE/CVF International Conference on Computer Vision (ICCV)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:2504.04029","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.04029","pdf_url":"https://arxiv.org/pdf/2504.04029","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2504.04029","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2504.04029","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2504.04029","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2504.04029","pdf_url":"https://arxiv.org/pdf/2504.04029","source":{"id":"https://openalex.org/S4393918464","display_name":"ArXiv.org","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G6510858048","display_name":null,"funder_award_id":"390523135","funder_id":"https://openalex.org/F4320320879","funder_display_name":"Deutsche Forschungsgemeinschaft"}],"funders":[{"id":"https://openalex.org/F4320320879","display_name":"Deutsche Forschungsgemeinschaft","ror":"https://ror.org/018mejw64"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Event":[0],"cameras":[1,17],"are":[2,18],"emerging":[3],"vision":[4],"sensors":[5],"whose":[6],"noise":[7],"is":[8,39,81],"challenging":[9],"to":[10,56],"characterize.":[11],"Existing":[12],"denoising":[13,120,143,148],"methods":[14],"for":[15],"event":[16,44],"often":[19],"designed":[20],"in":[21,69],"isolation":[22],"and":[23,77,122,135,145],"thus":[24],"consider":[25],"other":[26,99],"tasks,":[27],"such":[28,102],"as":[29,83,103],"motion":[30,38,68,89,100,133],"estimation,":[31],"separately":[32],"(i.e.,":[33],"sequentially":[34],"after":[35],"denoising).":[36],"However,":[37],"an":[40],"intrinsic":[41],"part":[42],"of":[43,59,91],"data,":[45],"since":[46],"scene":[47],"edges":[48],"cannot":[49],"be":[50],"sensed":[51],"without":[52],"motion.":[53],"We":[54],"propose,":[55],"the":[57,62,87,92,111,118,126],"best":[58],"our":[60],"knowledge,":[61],"first":[63],"method":[64,80,113],"that":[65,110],"simultaneously":[66],"estimates":[67],"its":[70],"various":[71],"forms":[72],"(e.g.,":[73],"ego-motion,":[74],"optical":[75],"flow)":[76],"noise.":[78],"The":[79,107],"flexible,":[82],"it":[84],"allows":[85],"replacing":[86],"one-step":[88],"estimation":[90,134],"widely-used":[93],"Contrast":[94],"Maximization":[95],"framework":[96],"with":[97],"any":[98],"estimator,":[101],"deep":[104],"neural":[105],"networks.":[106],"experiments":[108],"show":[109],"proposed":[112],"achieves":[114],"state-of-the-art":[115],"results":[116,124],"on":[117,125],"E-MLB":[119],"benchmark":[121],"competitive":[123],"DND21":[127],"benchmark,":[128],"while":[129],"demonstrating":[130],"effectiveness":[131],"across":[132],"intensity":[136],"reconstruction":[137],"tasks.":[138],"Our":[139],"approach":[140],"advances":[141],"event-data":[142],"theory":[144],"expands":[146],"practical":[147],"use-cases":[149],"via":[150],"open-source":[151],"code.":[152],"Project":[153],"page:":[154],"https://github.com/tub-rip/ESMD":[155]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}