Video super-resolution using wave-shape network

研究成果: Conference contribution

抄録

Video super-resolution (VSR) aims to restore a high-resolution (HR) image from multiple low-resolution (LR) frames. Previous works deal with inputs LR frames by stacking or warping and only use single scale features for reconstruction. Most of them didn't consider fusing multi-scale spatial and inter-frame temporal information, which may result in loss of details. In this paper, a novel architecture named Wave-shape network is proposed, which is designed to treat each frame as a separate source of information and fuse different temporal frames through a multi-scale structure. This fusion strategy enables us to capture more complete structure and context information for HR image quality improvement. We evaluate this model on Vid4 dataset and the results show Waveshape network not only achieves significant improvement in vision but also obtains much higher PSNR and SSIM than most previous VSR methods.

本文言語English
ホスト出版物のタイトルProceedings of the 2019 3rd International Conference on Video and Image Processing, ICVIP 2019
出版社Association for Computing Machinery
ページ132-136
ページ数5
ISBN(電子版)9781450376822
DOI
出版ステータスPublished - 2019 12 20
イベント3rd International Conference on Video and Image Processing, ICVIP 2019 - Shanghai, China
継続期間: 2019 12 202019 12 23

出版物シリーズ

名前ACM International Conference Proceeding Series

Conference

Conference3rd International Conference on Video and Image Processing, ICVIP 2019
CountryChina
CityShanghai
Period19/12/2019/12/23

ASJC Scopus subject areas

  • Software
  • Human-Computer Interaction
  • Computer Vision and Pattern Recognition
  • Computer Networks and Communications

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