Multi-Scale Warping for Video Frame Interpolation
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Choi, Whan | - |
dc.contributor.author | Koh, Yeong Jun | - |
dc.contributor.author | Kim, Chang-Su | - |
dc.date.accessioned | 2022-03-12T00:40:31Z | - |
dc.date.available | 2022-03-12T00:40:31Z | - |
dc.date.created | 2022-01-20 | - |
dc.date.issued | 2021 | - |
dc.identifier.issn | 2169-3536 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/138658 | - |
dc.description.abstract | A novel video interpolation network to improve the temporal resolutions of video sequences is proposed in this work. We develop a multi-scale warping module to interpolate intermediate frames robustly for both small and large motions. Specifically, the proposed multi-scale warping module deals with large motions between two consecutive frames using coarse-scale features, while estimating detailed local motions by exploring fine-scale features. To this end, it takes multi-scale features from the encoder and estimates kernel weights and offset vectors for each scale. Finally, it synthesizes multi-scale warping frames and combines them to obtain an intermediate frame. Extensive experimental results demonstrate that the proposed algorithm outperforms state-of-the-art video interpolation algorithms on various benchmark datasets. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | MOTION ESTIMATION | - |
dc.title | Multi-Scale Warping for Video Frame Interpolation | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Chang-Su | - |
dc.identifier.doi | 10.1109/ACCESS.2021.3126593 | - |
dc.identifier.scopusid | 2-s2.0-85119585894 | - |
dc.identifier.wosid | 000717750400001 | - |
dc.identifier.bibliographicCitation | IEEE ACCESS, v.9, pp.150470 - 150479 | - |
dc.relation.isPartOf | IEEE ACCESS | - |
dc.citation.title | IEEE ACCESS | - |
dc.citation.volume | 9 | - |
dc.citation.startPage | 150470 | - |
dc.citation.endPage | 150479 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | MOTION ESTIMATION | - |
dc.subject.keywordAuthor | Interpolation | - |
dc.subject.keywordAuthor | Kernel | - |
dc.subject.keywordAuthor | Feature extraction | - |
dc.subject.keywordAuthor | Convolution | - |
dc.subject.keywordAuthor | Adaptive optics | - |
dc.subject.keywordAuthor | Streaming media | - |
dc.subject.keywordAuthor | Optical imaging | - |
dc.subject.keywordAuthor | Video frame interpolation | - |
dc.subject.keywordAuthor | convolutional neural network | - |
dc.subject.keywordAuthor | multi-scale feature | - |
dc.subject.keywordAuthor | kernel-based approach | - |
dc.subject.keywordAuthor | deformable convolution | - |
dc.subject.keywordAuthor | adaptive convolution | - |
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