Multi-Scale Warping for Video Frame Interpolation
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...
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2021
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oai:doaj.org-article:00b115b6a41347b8a4105aa0d1a77cc92021-11-18T00:08:26ZMulti-Scale Warping for Video Frame Interpolation2169-353610.1109/ACCESS.2021.3126593https://doaj.org/article/00b115b6a41347b8a4105aa0d1a77cc92021-01-01T00:00:00Zhttps://ieeexplore.ieee.org/document/9606905/https://doaj.org/toc/2169-3536A 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.Whan ChoiYeong Jun KohChang-Su KimIEEEarticleVideo frame interpolationconvolutional neural networkmulti-scale featurekernel-based approachdeformable convolutionadaptive convolutionElectrical engineering. Electronics. Nuclear engineeringTK1-9971ENIEEE Access, Vol 9, Pp 150470-150479 (2021) |
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language |
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Video frame interpolation convolutional neural network multi-scale feature kernel-based approach deformable convolution adaptive convolution Electrical engineering. Electronics. Nuclear engineering TK1-9971 |
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Video frame interpolation convolutional neural network multi-scale feature kernel-based approach deformable convolution adaptive convolution Electrical engineering. Electronics. Nuclear engineering TK1-9971 Whan Choi Yeong Jun Koh Chang-Su Kim Multi-Scale Warping for Video Frame Interpolation |
description |
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. |
format |
article |
author |
Whan Choi Yeong Jun Koh Chang-Su Kim |
author_facet |
Whan Choi Yeong Jun Koh Chang-Su Kim |
author_sort |
Whan Choi |
title |
Multi-Scale Warping for Video Frame Interpolation |
title_short |
Multi-Scale Warping for Video Frame Interpolation |
title_full |
Multi-Scale Warping for Video Frame Interpolation |
title_fullStr |
Multi-Scale Warping for Video Frame Interpolation |
title_full_unstemmed |
Multi-Scale Warping for Video Frame Interpolation |
title_sort |
multi-scale warping for video frame interpolation |
publisher |
IEEE |
publishDate |
2021 |
url |
https://doaj.org/article/00b115b6a41347b8a4105aa0d1a77cc9 |
work_keys_str_mv |
AT whanchoi multiscalewarpingforvideoframeinterpolation AT yeongjunkoh multiscalewarpingforvideoframeinterpolation AT changsukim multiscalewarpingforvideoframeinterpolation |
_version_ |
1718425202972426240 |