{"id":"https://openalex.org/W7154684994","doi":"https://doi.org/10.48550/arxiv.2604.15312","title":"Bidirectional Cross-Modal Prompting for Event-Frame Asymmetric Stereo","display_name":"Bidirectional Cross-Modal Prompting for Event-Frame Asymmetric Stereo","publication_year":2026,"publication_date":"2026-04-16","ids":{"openalex":"https://openalex.org/W7154684994","doi":"https://doi.org/10.48550/arxiv.2604.15312"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2604.15312","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15312","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":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2604.15312","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5049098728","display_name":"Ninghui Xu","orcid":"https://orcid.org/0000-0002-0652-2788"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Xu, Ninghui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133864590","display_name":"Fabio Tosi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tosi, Fabio","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133899366","display_name":"Lihui Wang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Lihui","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133840397","display_name":"Jiawei Han","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Han, Jiawei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133828493","display_name":"Luca Bartolomei","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bartolomei, Luca","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5075450730","display_name":"Zhiting Yao","orcid":"https://orcid.org/0000-0002-9570-4312"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yao, Zhiting","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5133860167","display_name":"Matteo Poggi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Poggi, Matteo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5072569849","display_name":"Stefano Mattoccia","orcid":"https://orcid.org/0000-0002-3681-7704"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Mattoccia, Stefano","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":8,"corresponding_author_ids":["https://openalex.org/A5049098728"],"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":0.9368000030517578,"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":0.9368000030517578,"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":0.020099999383091927,"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":0.004000000189989805,"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/representation","display_name":"Representation (politics)","score":0.5874000191688538},{"id":"https://openalex.org/keywords/event","display_name":"Event (particle physics)","score":0.5310999751091003},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4763000011444092},{"id":"https://openalex.org/keywords/motion","display_name":"Motion (physics)","score":0.46619999408721924},{"id":"https://openalex.org/keywords/modality","display_name":"Modality (human\u2013computer interaction)","score":0.45489999651908875},{"id":"https://openalex.org/keywords/perception","display_name":"Perception","score":0.44369998574256897},{"id":"https://openalex.org/keywords/stereopsis","display_name":"Stereopsis","score":0.4377000033855438},{"id":"https://openalex.org/keywords/frame","display_name":"Frame (networking)","score":0.4291999936103821},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.36800000071525574}],"concepts":[{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7764999866485596},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.7741000056266785},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7177000045776367},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5874000191688538},{"id":"https://openalex.org/C2779662365","wikidata":"https://www.wikidata.org/wiki/Q5416694","display_name":"Event (particle physics)","level":2,"score":0.5310999751091003},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4763000011444092},{"id":"https://openalex.org/C104114177","wikidata":"https://www.wikidata.org/wiki/Q79782","display_name":"Motion (physics)","level":2,"score":0.46619999408721924},{"id":"https://openalex.org/C2780226545","wikidata":"https://www.wikidata.org/wiki/Q6888030","display_name":"Modality (human\u2013computer interaction)","level":2,"score":0.45489999651908875},{"id":"https://openalex.org/C26760741","wikidata":"https://www.wikidata.org/wiki/Q160402","display_name":"Perception","level":2,"score":0.44369998574256897},{"id":"https://openalex.org/C68537008","wikidata":"https://www.wikidata.org/wiki/Q247932","display_name":"Stereopsis","level":2,"score":0.4377000033855438},{"id":"https://openalex.org/C126042441","wikidata":"https://www.wikidata.org/wiki/Q1324888","display_name":"Frame (networking)","level":2,"score":0.4291999936103821},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.36800000071525574},{"id":"https://openalex.org/C3004257","wikidata":"https://www.wikidata.org/wiki/Q17084606","display_name":"Correspondence problem","level":2,"score":0.36000001430511475},{"id":"https://openalex.org/C2780056265","wikidata":"https://www.wikidata.org/wiki/Q106239881","display_name":"High dynamic range","level":3,"score":0.3312000036239624},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.3010999858379364},{"id":"https://openalex.org/C204323151","wikidata":"https://www.wikidata.org/wiki/Q905424","display_name":"Range (aeronautics)","level":2,"score":0.299699991941452},{"id":"https://openalex.org/C10161872","wikidata":"https://www.wikidata.org/wiki/Q557891","display_name":"Motion estimation","level":2,"score":0.28049999475479126},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.2741999924182892},{"id":"https://openalex.org/C35861506","wikidata":"https://www.wikidata.org/wiki/Q17141434","display_name":"Stereo cameras","level":3,"score":0.2703000009059906},{"id":"https://openalex.org/C119666444","wikidata":"https://www.wikidata.org/wiki/Q5977280","display_name":"Temporal resolution","level":2,"score":0.2662000060081482},{"id":"https://openalex.org/C31451488","wikidata":"https://www.wikidata.org/wiki/Q5157586","display_name":"Computer stereo vision","level":3,"score":0.2606000006198883},{"id":"https://openalex.org/C48007421","wikidata":"https://www.wikidata.org/wiki/Q676252","display_name":"Motion capture","level":3,"score":0.25929999351501465},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.2590999901294708},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.2565000057220459},{"id":"https://openalex.org/C172849965","wikidata":"https://www.wikidata.org/wiki/Q3148875","display_name":"Reference frame","level":3,"score":0.2529999911785126},{"id":"https://openalex.org/C146159030","wikidata":"https://www.wikidata.org/wiki/Q7625099","display_name":"Structure from motion","level":3,"score":0.25130000710487366},{"id":"https://openalex.org/C2779903281","wikidata":"https://www.wikidata.org/wiki/Q6888026","display_name":"Modalities","level":2,"score":0.2500999867916107}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2604.15312","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15312","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":"doi:10.48550/arxiv.2604.15312","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2604.15312","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":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"score":0.7886651158332825,"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Conventional":[0],"frame-based":[1],"cameras":[2,20],"capture":[3],"rich":[4],"contextual":[5],"information":[6],"but":[7],"suffer":[8],"from":[9,31,91],"limited":[10],"temporal":[11],"resolution":[12],"and":[13,53,88,109,120,135],"motion":[14,52],"blur":[15],"in":[16,133],"dynamic":[17,28],"scenes.":[18],"Event":[19],"offer":[21],"an":[22],"alternative":[23],"visual":[24],"representation":[25],"with":[26],"higher":[27],"range":[29],"free":[30],"such":[32],"limitations.":[33],"The":[34],"complementary":[35,111],"characteristics":[36],"of":[37,64],"the":[38,57],"two":[39],"modalities":[40],"make":[41],"event-frame":[42],"asymmetric":[43],"stereo":[44,70,102],"promising":[45],"for":[46,68,94],"reliable":[47],"3D":[48],"perception":[49],"under":[50],"fast":[51],"challenging":[54],"illumination.":[55],"However,":[56],"modality":[58,116],"gap":[59],"often":[60],"leads":[61],"to":[62],"marginalization":[63],"domain-specific":[65],"cues":[66],"essential":[67],"cross-modal":[69,81],"matching.":[71,96],"In":[72],"this":[73],"paper,":[74],"we":[75],"introduce":[76],"Bi-CMPStereo,":[77],"a":[78,105],"novel":[79],"bidirectional":[80],"prompting":[82],"framework":[83],"that":[84,126],"fully":[85],"exploits":[86],"semantic":[87],"structural":[89],"features":[90],"both":[92,118],"domains":[93],"robust":[95],"Our":[97],"approach":[98,128],"learns":[99],"finely":[100],"aligned":[101],"representations":[103,112],"within":[104],"target":[106],"canonical":[107],"space":[108],"integrates":[110],"by":[113],"projecting":[114],"each":[115],"into":[117],"event":[119],"frame":[121],"domains.":[122],"Extensive":[123],"experiments":[124],"demonstrate":[125],"our":[127],"significantly":[129],"outperforms":[130],"state-of-the-art":[131],"methods":[132],"accuracy":[134],"generalization.":[136]},"counts_by_year":[],"updated_date":"2026-04-18T06:05:20.339008","created_date":"2026-04-18T00:00:00"}