{"id":"https://openalex.org/W4284976507","doi":"https://doi.org/10.48550/arxiv.2207.03038","title":"Dual-Stream Transformer for Generic Event Boundary Captioning","display_name":"Dual-Stream Transformer for Generic Event Boundary Captioning","publication_year":2022,"publication_date":"2022-07-07","ids":{"openalex":"https://openalex.org/W4284976507","doi":"https://doi.org/10.48550/arxiv.2207.03038"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2207.03038","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.03038","pdf_url":"https://arxiv.org/pdf/2207.03038","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2207.03038","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5057558573","display_name":"Xin Gu","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Gu, Xin","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5045051320","display_name":"Hanhua Ye","orcid":"https://orcid.org/0009-0006-0824-6306"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ye, Hanhua","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102992722","display_name":"Guang Chen","orcid":"https://orcid.org/0000-0003-1487-8044"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Guang","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100374818","display_name":"Yufei Wang","orcid":"https://orcid.org/0000-0002-0729-908X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wang, Yufei","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100337167","display_name":"Libo Zhang","orcid":"https://orcid.org/0000-0002-7153-6465"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhang, Libo","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5018942445","display_name":"Longyin Wen","orcid":"https://orcid.org/0000-0001-5525-492X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wen, Longyin","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":6,"corresponding_author_ids":["https://openalex.org/A5057558573"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":2,"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/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":0.9998999834060669,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T11439","display_name":"Video Analysis and Summarization","score":0.9973999857902527,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/T10812","display_name":"Human Pose and Action Recognition","score":0.9940999746322632,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"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/closed-captioning","display_name":"Closed captioning","score":0.9852110147476196},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7878959774971008},{"id":"https://openalex.org/keywords/transformer","display_name":"Transformer","score":0.7451168298721313},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.6952398419380188},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.48365864157676697},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.41302740573883057},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3730178475379944},{"id":"https://openalex.org/keywords/voltage","display_name":"Voltage","score":0.1275966763496399},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.11664563417434692},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10829707980155945}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.9852110147476196},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7878959774971008},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7451168298721313},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.6952398419380188},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.48365864157676697},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.41302740573883057},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3730178475379944},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.1275966763496399},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.11664563417434692},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10829707980155945},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2207.03038","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.03038","pdf_url":"https://arxiv.org/pdf/2207.03038","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},{"id":"doi:10.48550/arxiv.2207.03038","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2207.03038","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:2207.03038","is_oa":true,"landing_page_url":"http://arxiv.org/abs/2207.03038","pdf_url":"https://arxiv.org/pdf/2207.03038","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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"","raw_type":null},"sustainable_development_goals":[{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.7300000190734863}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W4290852288","https://openalex.org/W4310447809","https://openalex.org/W4200243030","https://openalex.org/W2800782462","https://openalex.org/W3209117276","https://openalex.org/W4388184981","https://openalex.org/W4323777661"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"our":[3,138],"champion":[4],"solution":[5],"for":[6,105],"the":[7,17,29,70,79,87,117,130,135],"CVPR2022":[8],"Generic":[9],"Event":[10],"Boundary":[11],"Captioning":[12],"(GEBC)":[13],"competition.":[14],"GEBC":[15,131],"requires":[16],"captioning":[18,42],"model":[19,88],"to":[20,68,85,101],"have":[21],"a":[22,47,122],"comprehension":[23],"of":[24,81,137],"instantaneous":[25],"status":[26],"changes":[27],"around":[28],"given":[30],"video":[31,41,54,71],"boundary,":[32],"which":[33],"makes":[34],"it":[35],"much":[36],"more":[37],"challenging":[38],"than":[39],"conventional":[40],"task.":[43],"In":[44],"this":[45],"paper,":[46],"Dual-Stream":[48,99],"Transformer":[49],"with":[50],"improvements":[51],"on":[52,129],"both":[53],"content":[55],"encoding":[56],"and":[57,112],"captions":[58],"generation":[59],"is":[60],"proposed:":[61],"(1)":[62],"We":[63,92],"utilize":[64],"three":[65],"pre-trained":[66],"models":[67],"extract":[69],"features":[72],"from":[73],"different":[74],"granularities.":[75],"Moreover,":[76],"we":[77,115],"exploit":[78],"types":[80],"boundary":[82,106],"as":[83,98],"hints":[84],"help":[86],"generate":[89],"captions.":[90],"(2)":[91],"particularly":[93],"design":[94],"an":[95],"model,":[96],"termed":[97],"Transformer,":[100],"learn":[102],"discriminative":[103],"representations":[104],"captioning.":[107],"(3)":[108],"Towards":[109],"generating":[110],"content-relevant":[111],"human-like":[113],"captions,":[114],"improve":[116],"description":[118],"quality":[119],"by":[120],"designing":[121],"word-level":[123],"ensemble":[124],"strategy.":[125],"The":[126],"promising":[127],"results":[128],"test":[132],"split":[133],"demonstrate":[134],"efficacy":[136],"proposed":[139],"model.":[140]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}
