Video Frame Interpolation Via Residue Refinement

Haopeng Li, Yuan Yuan, Qi Wang

科研成果: 书/报告/会议事项章节会议稿件同行评审

58 引用 (Scopus)

摘要

Video frame interpolation achieves temporal super-resolution by generating smooth transitions between frames. Although great success has been achieved by deep neural networks, the synthesized images stills suffer from poor visual appearance and unsatisfactory artifacts. In this paper, we propose a novel network structure that leverages residue refinement and adaptive weight to synthesize in-between frames. The residue refinement technique is used for optical flow and image generation for higher accuracy and better visual appearance, while the adaptive weight map combines the forward and backward warped frames to reduce the artifacts. Moreover, all submodules in our method are implemented by U-Net with less depths, so the efficiency is guaranteed. Experiments on public datasets demonstrate the effectiveness and superiority of our method over the state-of-the-art approaches.

源语言英语
主期刊名2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
出版商Institute of Electrical and Electronics Engineers Inc.
2613-2617
页数5
ISBN(电子版)9781509066315
DOI
出版状态已出版 - 5月 2020
活动2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, 西班牙
期限: 4 5月 20208 5月 2020

出版系列

姓名ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
2020-May
ISSN(印刷版)1520-6149

会议

会议2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
国家/地区西班牙
Barcelona
时期4/05/208/05/20

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