{"id":"https://openalex.org/W7161735862","doi":"https://doi.org/10.48550/arxiv.2605.17984","title":"See Silhouettes in Motion with Neuromorphic Vision","display_name":"See Silhouettes in Motion with Neuromorphic Vision","publication_year":2026,"publication_date":"2026-05-18","ids":{"openalex":"https://openalex.org/W7161735862","doi":"https://doi.org/10.48550/arxiv.2605.17984"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2605.17984","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17984","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2605.17984","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5136503302","display_name":"Pei Zhang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Pei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136459849","display_name":"Shijie Lin","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lin, Shijie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136499378","display_name":"Zhou Ge","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ge, Zhou","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5136494429","display_name":"Jinpeng Chen","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Jinpeng","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5136489474","display_name":"Wei Pu","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Pu, Wei","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"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":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10502","display_name":"Advanced Memory and Neural Computing","score":0.8747000098228455,"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":0.8747000098228455,"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":0.044599998742341995,"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"}},{"id":"https://openalex.org/T12808","display_name":"Ferroelectric and Negative Capacitance Devices","score":0.02539999969303608,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/neuromorphic-engineering","display_name":"Neuromorphic engineering","score":0.7835999727249146},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.5483999848365784},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5209000110626221},{"id":"https://openalex.org/keywords/workflow","display_name":"Workflow","score":0.4975999891757965},{"id":"https://openalex.org/keywords/asynchronous-communication","display_name":"Asynchronous communication","score":0.4869999885559082},{"id":"https://openalex.org/keywords/motion-blur","display_name":"Motion blur","score":0.47279998660087585},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.460099995136261},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.42649999260902405},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.41040000319480896}],"concepts":[{"id":"https://openalex.org/C151927369","wikidata":"https://www.wikidata.org/wiki/Q1981312","display_name":"Neuromorphic engineering","level":3,"score":0.7835999727249146},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.756600022315979},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.6901000142097473},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6496999859809875},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.5483999848365784},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5209000110626221},{"id":"https://openalex.org/C177212765","wikidata":"https://www.wikidata.org/wiki/Q627335","display_name":"Workflow","level":2,"score":0.4975999891757965},{"id":"https://openalex.org/C151319957","wikidata":"https://www.wikidata.org/wiki/Q752739","display_name":"Asynchronous communication","level":2,"score":0.4869999885559082},{"id":"https://openalex.org/C2777708103","wikidata":"https://www.wikidata.org/wiki/Q852589","display_name":"Motion blur","level":3,"score":0.47279998660087585},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.460099995136261},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.42649999260902405},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.41040000319480896},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.37540000677108765},{"id":"https://openalex.org/C12713177","wikidata":"https://www.wikidata.org/wiki/Q1900281","display_name":"Perspective (graphical)","level":2,"score":0.3589000105857849},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.35690000653266907},{"id":"https://openalex.org/C50637493","wikidata":"https://www.wikidata.org/wiki/Q1136781","display_name":"Morphing","level":2,"score":0.33009999990463257},{"id":"https://openalex.org/C155542232","wikidata":"https://www.wikidata.org/wiki/Q736111","display_name":"Optical flow","level":3,"score":0.32089999318122864},{"id":"https://openalex.org/C2780719617","wikidata":"https://www.wikidata.org/wiki/Q1030752","display_name":"Salient","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C3261483","wikidata":"https://www.wikidata.org/wiki/Q119565","display_name":"Frame rate","level":2,"score":0.3142000138759613},{"id":"https://openalex.org/C5339829","wikidata":"https://www.wikidata.org/wiki/Q1425977","display_name":"Machine vision","level":2,"score":0.3043000102043152},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.2913999855518341},{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.29010000824928284},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.28760001063346863},{"id":"https://openalex.org/C13662910","wikidata":"https://www.wikidata.org/wiki/Q193139","display_name":"Trajectory","level":2,"score":0.28540000319480896},{"id":"https://openalex.org/C162307627","wikidata":"https://www.wikidata.org/wiki/Q204833","display_name":"Enhanced Data Rates for GSM Evolution","level":2,"score":0.2777000069618225},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.2653999924659729},{"id":"https://openalex.org/C774472","wikidata":"https://www.wikidata.org/wiki/Q6760393","display_name":"Margin (machine learning)","level":2,"score":0.26510000228881836},{"id":"https://openalex.org/C45347329","wikidata":"https://www.wikidata.org/wiki/Q5166604","display_name":"Convolution (computer science)","level":3,"score":0.2635999917984009},{"id":"https://openalex.org/C2780624872","wikidata":"https://www.wikidata.org/wiki/Q852453","display_name":"Motion detection","level":3,"score":0.2542000114917755},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.25360000133514404}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2605.17984","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17984","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2605.17984","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2605.17984","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":false,"raw_source_name":null,"raw_type":"Preprint"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Quasi-bimodal":[0],"objects,":[1],"such":[2],"as":[3,107,199],"text,":[4],"road":[5],"signs,":[6],"and":[7,69,80,101,130,155,217],"barcodes,":[8],"play":[9],"a":[10,28,108,118,163,204],"basic":[11],"yet":[12,120],"vital":[13],"role":[14],"in":[15,72,106,151,219],"daily":[16],"visual":[17],"communication.":[18],"By":[19],"boiling":[20],"these":[21,89],"down":[22],"to":[23,31,202],"clear":[24,185],"silhouettes,":[25],"binarization":[26,136],"uses":[27],"minimal":[29],"language":[30],"convey":[32],"essential":[33],"vision":[34,93],"cues":[35],"for":[36,41,132],"maximum":[37],"downstream":[38,207],"efficiency,":[39],"especially":[40],"tasks":[42],"that":[43,57,124,143,175],"require":[44],"simple":[45,119],"geometric,":[46],"topological":[47],"reasoning":[48],"rather":[49],"than":[50],"heavy":[51],"appearance":[52],"modeling.":[53],"The":[54],"catch":[55],"is":[56],"frame-based":[58],"imaging":[59],"often":[60],"struggles":[61],"on":[62,137,222],"mobile":[63],"platforms":[64],"like":[65],"drones,":[66],"self-driving":[67],"cars,":[68],"underwater":[70],"vehicles,":[71],"which":[73],"rapid":[74],"motion":[75,78],"causes":[76],"severe":[77],"blur":[79,153],"harsh":[81],"lighting":[82],"washes":[83],"out":[84],"scene":[85],"details.":[86],"To":[87],"overcome":[88],"physical":[90],"limits,":[91],"neuromorphic":[92],"via":[94],"event":[95],"cameras,":[96],"featuring":[97],"microsecond":[98],"time":[99,182],"resolution":[100],"high":[102],"dynamic":[103],"range,":[104],"steps":[105],"natural":[109],"solution.":[110],"Building":[111],"upon":[112],"this":[113],"event-driven":[114],"paradigm,":[115],"we":[116],"propose":[117],"effective":[121],"dual-modal":[122],"approach":[123],"harnesses":[125],"the":[126,212],"synergy":[127],"between":[128],"frames":[129],"events":[131],"training-free,":[133],"real-time,":[134],"high-frame-rate":[135],"CPU-only":[138],"devices.":[139],"Extensive":[140],"evaluations":[141],"show":[142],"it":[144],"earns":[145],"competitive":[146],"performance":[147],"against":[148],"leading":[149],"techniques":[150],"reducing":[152],"artifacts":[154],"delivers":[156],"impressive":[157],"improvements":[158],"under":[159],"challenging":[160],"illumination":[161],"at":[162,180,189],"lower":[164],"computational":[165],"cost.":[166],"Besides,":[167],"its":[168],"asynchronous":[169],"nature":[170],"bypasses":[171],"long-standing":[172],"event-scarcity":[173],"issues":[174],"break":[176],"traditional":[177],"time-binning":[178],"reconstruction":[179],"fixed":[181],"slots,":[183],"maintaining":[184],"target":[186],"shapes":[187],"even":[188],"extreme":[190],"kilohertz":[191],"frame":[192],"rates.":[193],"Its":[194],"binary":[195],"results":[196],"further":[197],"serve":[198],"reliable":[200],"representations":[201],"facilitate":[203],"range":[205],"of":[206],"tasks.":[208],"This":[209],"work":[210],"paves":[211],"way":[213],"towards":[214],"lightweight":[215],"perception":[216],"interaction":[218],"embodied":[220],"intelligence":[221],"resource-constrained":[223],"edge":[224],"platforms.":[225]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-05-20T00:00:00"}