{"id":"https://openalex.org/W4402352169","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651205","title":"CLIP-based Semantic Enhancement and Vocabulary Expansion for Video Captioning Using Reinforcement Learning","display_name":"CLIP-based Semantic Enhancement and Vocabulary Expansion for Video Captioning Using Reinforcement Learning","publication_year":2024,"publication_date":"2024-06-30","ids":{"openalex":"https://openalex.org/W4402352169","doi":"https://doi.org/10.1109/ijcnn60899.2024.10651205"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn60899.2024.10651205","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 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/A5080267508","display_name":"Lihuan Zheng","orcid":"https://orcid.org/0000-0002-8818-0434"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Lihuan Zheng","raw_affiliation_strings":["Beijing Jiaotong University,Institute of Information Science,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,Institute of Information Science,Beijing,China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5069488093","display_name":"Ping Guo","orcid":"https://orcid.org/0000-0003-0979-7047"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ping Guo","raw_affiliation_strings":["Intel,Intel Labs China,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Intel,Intel Labs China,Beijing,China","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5109778674","display_name":"Zhenjiao Miao","orcid":null},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Zhenjiao Miao","raw_affiliation_strings":["Beijing Jiaotong University,Institute of Information Science,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,Institute of Information Science,Beijing,China","institution_ids":["https://openalex.org/I21193070"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5071889746","display_name":"Wanru Xu","orcid":"https://orcid.org/0000-0003-2206-5051"},"institutions":[{"id":"https://openalex.org/I21193070","display_name":"Beijing Jiaotong University","ror":"https://ror.org/01yj56c84","country_code":"CN","type":"education","lineage":["https://openalex.org/I21193070"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Wanru Xu","raw_affiliation_strings":["Beijing Jiaotong University,Institute of Information Science,Beijing,China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Jiaotong University,Institute of Information Science,Beijing,China","institution_ids":["https://openalex.org/I21193070"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"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":0.1668572,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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/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/T10812","display_name":"Human Pose and Action Recognition","score":0.9961000084877014,"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":0.9901999831199646,"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":0.9342879056930542},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8348231315612793},{"id":"https://openalex.org/keywords/reinforcement-learning","display_name":"Reinforcement learning","score":0.791074275970459},{"id":"https://openalex.org/keywords/vocabulary","display_name":"Vocabulary","score":0.6528600454330444},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4603078365325928},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.45352277159690857},{"id":"https://openalex.org/keywords/english-vocabulary","display_name":"English vocabulary","score":0.42001450061798096},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.3295506238937378},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.12450748682022095},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.08337453007698059}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.9342879056930542},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8348231315612793},{"id":"https://openalex.org/C97541855","wikidata":"https://www.wikidata.org/wiki/Q830687","display_name":"Reinforcement learning","level":2,"score":0.791074275970459},{"id":"https://openalex.org/C2777601683","wikidata":"https://www.wikidata.org/wiki/Q6499736","display_name":"Vocabulary","level":2,"score":0.6528600454330444},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4603078365325928},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.45352277159690857},{"id":"https://openalex.org/C3017914614","wikidata":"https://www.wikidata.org/wiki/Q1860","display_name":"English vocabulary","level":3,"score":0.42001450061798096},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.3295506238937378},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.12450748682022095},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.08337453007698059},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ijcnn60899.2024.10651205","is_oa":false,"landing_page_url":"http://dx.doi.org/10.1109/ijcnn60899.2024.10651205","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.5600000023841858}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":51,"referenced_works":["https://openalex.org/W1586939924","https://openalex.org/W1601567445","https://openalex.org/W1607035479","https://openalex.org/W1956340063","https://openalex.org/W2101105183","https://openalex.org/W2139501017","https://openalex.org/W2142900973","https://openalex.org/W2154652894","https://openalex.org/W2176263492","https://openalex.org/W2425121537","https://openalex.org/W2525778437","https://openalex.org/W2556388456","https://openalex.org/W2561529111","https://openalex.org/W2600463316","https://openalex.org/W2612675303","https://openalex.org/W2896012058","https://openalex.org/W2948358897","https://openalex.org/W2963084599","https://openalex.org/W2963477107","https://openalex.org/W2963524571","https://openalex.org/W2963877622","https://openalex.org/W2963971014","https://openalex.org/W2964303913","https://openalex.org/W2972281329","https://openalex.org/W2979747405","https://openalex.org/W2981750519","https://openalex.org/W2984008963","https://openalex.org/W3035365026","https://openalex.org/W3035372819","https://openalex.org/W3035392611","https://openalex.org/W3035454069","https://openalex.org/W3174476431","https://openalex.org/W3176425931","https://openalex.org/W3176689360","https://openalex.org/W3192261211","https://openalex.org/W3205021045","https://openalex.org/W3205898187","https://openalex.org/W4241811150","https://openalex.org/W4285606530","https://openalex.org/W4293363567","https://openalex.org/W4313033760","https://openalex.org/W4385245566","https://openalex.org/W4394659899","https://openalex.org/W6678262379","https://openalex.org/W6682631176","https://openalex.org/W6684090549","https://openalex.org/W6685322675","https://openalex.org/W6727690538","https://openalex.org/W6737479944","https://openalex.org/W6791353385","https://openalex.org/W6864544085"],"related_works":["https://openalex.org/W2360092643","https://openalex.org/W2273809206","https://openalex.org/W2390152745","https://openalex.org/W2391426744","https://openalex.org/W2380583786","https://openalex.org/W2368150256","https://openalex.org/W2350879667","https://openalex.org/W2381802581","https://openalex.org/W2370165242","https://openalex.org/W2353912367"],"abstract_inverted_index":{"Video":[0],"captioning":[1,35,68],"aims":[2],"to":[3,22,39,81,86,126],"comprehend":[4],"the":[5,44,77,83,98,111,120,151],"content":[6],"of":[7,123],"videos":[8,42,101],"and":[9,27,43,55,75,90,102,114,138,148],"automatically":[10],"generate":[11,87],"sentences.":[12,32,94],"It":[13],"necessitates":[14],"a":[15,18,106],"network":[16,109],"with":[17],"robust":[19],"knowledge":[20,45,79,147],"background":[21],"understand":[23],"complex":[24],"video":[25,34,61,67],"events":[26],"transform":[28],"them":[29],"into":[30],"coherent":[31],"Traditional":[33],"is":[36,46,170],"often":[37],"limited":[38],"modeling":[40],"close-domain":[41],"fixed":[47],"after":[48],"training,":[49],"which":[50],"results":[51],"in":[52,155],"generating":[53],"short":[54],"uninformative":[56],"captions.":[57],"Different":[58],"from":[59,119],"traditional":[60],"captioning,":[62],"we":[63],"propose":[64],"an":[65],"open-domain":[66],"method":[69,169],"that":[70,166],"incorporates":[71],"external":[72],"textual":[73],"data":[74],"expands":[76],"current":[78],"domain":[80],"enhance":[82],"model\u2019s":[84],"ability":[85],"more":[88],"nuanced":[89],"contextually":[91],"relevant":[92],"descriptive":[93],"This":[95],"paper":[96],"reduces":[97],"gap":[99],"between":[100],"texts":[103],"by":[104],"employing":[105],"well-pretrained":[107],"CLIP":[108],"at":[110],"lexical":[112],"level":[113],"effectively":[115],"retrieves":[116],"pertinent":[117],"vocabularies":[118],"training":[121],"corpus":[122],"two":[124],"datasets":[125,164],"serve":[127],"as":[128,145],"prompts.":[129],"Our":[130],"model":[131],"utilizes":[132],"retrieval":[133],"words":[134],"through":[135],"implicit":[136,146],"augmentation":[137],"explicit":[139],"augmentation,":[140],"providing":[141],"additional":[142],"semantic":[143],"features":[144],"explicitly":[149],"updating":[150],"word":[152],"sampling":[153],"pool":[154],"reinforcement":[156],"learning.":[157],"The":[158],"experiments":[159],"conducted":[160],"on":[161],"several":[162],"benchmark":[163],"show":[165],"our":[167],"proposed":[168],"effective.":[171]},"counts_by_year":[],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}
