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Guest Editorial Introduction to the Special Section on Video and Language
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Mei, Tao | - |
dc.contributor.author | Corso, Jason J. | - |
dc.contributor.author | Kim, Gun Hee | - |
dc.contributor.author | Luo, Jiebo | - |
dc.contributor.author | Shen, Chunhua | - |
dc.contributor.author | Zhang, Hanwang | - |
dc.date.accessioned | 2022-06-24T07:03:41Z | - |
dc.date.available | 2022-06-24T07:03:41Z | - |
dc.date.created | 2022-05-09 | - |
dc.date.issued | 2022-01 | - |
dc.identifier.citation | IEEE Transactions on Circuits and Systems for Video Technology, Vol.32 No.1, pp.1-4 | - |
dc.identifier.issn | 1051-8215 | - |
dc.identifier.uri | https://hdl.handle.net/10371/184005 | - |
dc.description.abstract | Computer Vision (CV) and Natural Language Processing (NLP) are two most fundamental disciplines under a broad area of artificial intelligence (AI). CV is regarded as a field of research that explores the techniques to teach computers to see and understand digital content such as images and videos. NLP is a branch of linguistics that enables computers to process, interpret, and even generate human language. With the rise and development of deep learning over the past decade, there has been a steady momentum of innovation and breakthroughs that convincingly push the limits and improve the state-of-the-art of both vision and language modeling. An interesting observation is that the research in the two areas starts to interact, with a significant growth in both the volume of publications and extensive applications. Meanwhile, many previous experiences have shown that this can naturally build up the circle of human intelligence. | - |
dc.language | 영어 | - |
dc.publisher | Institute of Electrical and Electronics Engineers | - |
dc.title | Guest Editorial Introduction to the Special Section on Video and Language | - |
dc.type | Article | - |
dc.identifier.doi | 10.1109/TCSVT.2021.3137430 | - |
dc.citation.journaltitle | IEEE Transactions on Circuits and Systems for Video Technology | - |
dc.identifier.wosid | 000742183600002 | - |
dc.identifier.scopusid | 2-s2.0-85123753762 | - |
dc.citation.endpage | 4 | - |
dc.citation.number | 1 | - |
dc.citation.startpage | 1 | - |
dc.citation.volume | 32 | - |
dc.description.isOpenAccess | N | - |
dc.contributor.affiliatedAuthor | Kim, Gun Hee | - |
dc.type.docType | Editorial | - |
dc.description.journalClass | 1 | - |
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