{"id":"https://openalex.org/W2896874112","doi":"https://doi.org/10.1109/icme.2018.8486437","title":"Refining Attention: A Sequential Attention Model for Image Captioning","display_name":"Refining Attention: A Sequential Attention Model for Image Captioning","publication_year":2018,"publication_date":"2018-07-01","ids":{"openalex":"https://openalex.org/W2896874112","doi":"https://doi.org/10.1109/icme.2018.8486437","mag":"2896874112"},"language":"en","primary_location":{"id":"doi:10.1109/icme.2018.8486437","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2018.8486437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"},"type":"article","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/A5100386889","display_name":"Fang Fang","orcid":"https://orcid.org/0009-0007-0113-9134"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Fang Fang","raw_affiliation_strings":["Ministry of Education, Tongji University, Shanghai, P. R. China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5119247506","display_name":"Qinyu Li","orcid":"https://orcid.org/0009-0001-1519-0914"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Qinyu Li","raw_affiliation_strings":["Department of Computer Science and Technology, Tongji University, Shanghai, P. R. China"],"affiliations":[{"raw_affiliation_string":"Department of Computer Science and Technology, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058982350","display_name":"Hanli Wang","orcid":"https://orcid.org/0000-0002-9999-4871"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Hanli Wang","raw_affiliation_strings":["Ministry of Education, Tongji University, Shanghai, P. R. China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5102827532","display_name":"Pengjie Tang","orcid":"https://orcid.org/0000-0001-7523-0175"},"institutions":[{"id":"https://openalex.org/I116953780","display_name":"Tongji University","ror":"https://ror.org/03rc6as71","country_code":"CN","type":"education","lineage":["https://openalex.org/I116953780"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Pengjie Tang","raw_affiliation_strings":["Ministry of Education, Tongji University, Shanghai, P. R. China"],"affiliations":[{"raw_affiliation_string":"Ministry of Education, Tongji University, Shanghai, P. R. China","institution_ids":["https://openalex.org/I116953780"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5100386889"],"corresponding_institution_ids":["https://openalex.org/I116953780"],"apc_list":null,"apc_paid":null,"fwci":0.3134,"has_fulltext":false,"cited_by_count":5,"citation_normalized_percentile":{"value":0.62629214,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"39","issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11714","display_name":"Multimodal Machine Learning Applications","score":1.0,"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":1.0,"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/T10627","display_name":"Advanced Image and Video Retrieval Techniques","score":0.9977999925613403,"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/T11605","display_name":"Visual Attention and Saliency Detection","score":0.9922999739646912,"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":0.877672553062439},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8253874778747559},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.7190051674842834},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.6692476272583008},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6628335118293762},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6291629076004028},{"id":"https://openalex.org/keywords/abstraction","display_name":"Abstraction","score":0.598758339881897},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.560646653175354},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5161203145980835},{"id":"https://openalex.org/keywords/decoding-methods","display_name":"Decoding methods","score":0.47764456272125244},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.47282230854034424},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.38271331787109375},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.12822192907333374},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.12438729405403137},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.10591593384742737}],"concepts":[{"id":"https://openalex.org/C157657479","wikidata":"https://www.wikidata.org/wiki/Q2367247","display_name":"Closed captioning","level":3,"score":0.877672553062439},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8253874778747559},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.7190051674842834},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.6692476272583008},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6628335118293762},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6291629076004028},{"id":"https://openalex.org/C124304363","wikidata":"https://www.wikidata.org/wiki/Q673661","display_name":"Abstraction","level":2,"score":0.598758339881897},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.560646653175354},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5161203145980835},{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.47764456272125244},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.47282230854034424},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.38271331787109375},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.12822192907333374},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.12438729405403137},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.10591593384742737},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111472728","wikidata":"https://www.wikidata.org/wiki/Q9471","display_name":"Epistemology","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icme.2018.8486437","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icme.2018.8486437","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Multimedia and Expo (ICME)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.7699999809265137,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":38,"referenced_works":["https://openalex.org/W68733909","https://openalex.org/W92662927","https://openalex.org/W1514535095","https://openalex.org/W1811254738","https://openalex.org/W1861492603","https://openalex.org/W1895577753","https://openalex.org/W1897761818","https://openalex.org/W1905882502","https://openalex.org/W1956340063","https://openalex.org/W2064675550","https://openalex.org/W2095705004","https://openalex.org/W2097117768","https://openalex.org/W2101105183","https://openalex.org/W2123301721","https://openalex.org/W2130942839","https://openalex.org/W2143449221","https://openalex.org/W2149557440","https://openalex.org/W2194775991","https://openalex.org/W2220981600","https://openalex.org/W2302086703","https://openalex.org/W2550553598","https://openalex.org/W2552161745","https://openalex.org/W2560645892","https://openalex.org/W2564898401","https://openalex.org/W2949376505","https://openalex.org/W2962706528","https://openalex.org/W2964018924","https://openalex.org/W2964168617","https://openalex.org/W3103022576","https://openalex.org/W6630875275","https://openalex.org/W6638742206","https://openalex.org/W6639102338","https://openalex.org/W6639694449","https://openalex.org/W6674330103","https://openalex.org/W6678262379","https://openalex.org/W6679436768","https://openalex.org/W6681184217","https://openalex.org/W6898505805"],"related_works":["https://openalex.org/W4210416330","https://openalex.org/W2775506363","https://openalex.org/W3088136942","https://openalex.org/W4290852288","https://openalex.org/W2949362007","https://openalex.org/W4283207562","https://openalex.org/W2963177403","https://openalex.org/W2330246314","https://openalex.org/W2949522393","https://openalex.org/W3217195652"],"abstract_inverted_index":{"Visual":[0],"attention":[1,12,29,43,58,68,81],"is":[2,44,60,87],"widely":[3],"applied":[4],"to":[5,65,90],"image":[6],"captioning.":[7],"Previous":[8],"works":[9],"put":[10],"visual":[11,42,67,93],"and":[13,75,105,118,127],"linguistic":[14,50],"word":[15,35,84],"into":[16],"a":[17,56],"long":[18],"short-term":[19],"memory":[20],"network":[21],"together,":[22],"but":[23],"neglect":[24],"the":[25,38,71,77,92,102,110,122],"sequential":[26,57,73],"relation":[27,79],"of":[28,41,49,125],"at":[30,82],"different":[31,46],"time":[32],"steps":[33],"during":[34,95],"prediction.":[36],"Moreover,":[37],"abstraction":[39],"degree":[40],"usually":[45],"from":[47],"that":[48,109],"word.":[51],"To":[52],"address":[53],"these":[54],"issues,":[55],"model":[59,112],"proposed":[61,111],"in":[62],"this":[63],"work":[64],"handle":[66],"by":[69],"considering":[70],"corresponding":[72],"relation,":[74],"hence":[76],"internal":[78],"among":[80],"each":[83],"prediction":[85],"step":[86],"well":[88],"utilized":[89],"enhance":[91],"information":[94],"sentence":[96],"decoding.":[97],"The":[98],"experimental":[99],"results":[100],"on":[101,121],"benchmark":[103],"MSCOCO":[104],"Flickr30K":[106],"datasets":[107],"show":[108],"achieves":[113],"excellent":[114],"performances":[115],"with":[116],"108.1":[117],"34.9":[119],"respectively":[120],"evaluation":[123],"criteria":[124],"CIDEr":[126],"BLEU-4":[128],"for":[129],"MSCOCO.":[130]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2019,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}