ORCID Profile
0000-0002-6705-1326
Current Organisations
University of Adelaide
,
Xi’an University of Posts and Telecommunications
,
Northwestern Polytechnical University
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Publisher: ACM
Date: 23-09-2022
Publisher: Springer Science and Business Media LLC
Date: 15-12-2023
DOI: 10.1007/S40747-022-00944-X
Abstract: Video super-resolution (VSR) aims to recover the high-resolution (HR) contents from the low-resolution (LR) observations relying on compositing the spatial–temporal information in the LR frames. It is crucial to propagate and aggregate spatial–temporal information. Recently, while transformers show impressive performance on high-level vision tasks, few attempts have been made on image restoration, especially on VSR. In addition, previous transformers simultaneously process spatial–temporal information, easily synthesizing confused textures and high computational cost limit its development. Towards this end, we construct a novel bidirectional recurrent VSR architecture. Our model disentangles the task of learning spatial–temporal information into two easier sub-tasks, each sub-task focuses on propagating and aggregating specific information with a multi-scale transformer-based design, which alleviates the difficulty of learning. Additionally, an attention-guided motion compensation module is applied to get rid of the influence of misalignment between frames. Experiments on three widely used benchmark datasets show that, relying on superior feature correlation learning, the proposed network can outperform previous state-of-the-art methods, especially for recovering the fine details.
Publisher: Elsevier BV
Date: 08-2020
Publisher: Springer International Publishing
Date: 2017
Publisher: Elsevier BV
Date: 06-2022
Publisher: Elsevier BV
Date: 09-2020
Publisher: Elsevier BV
Date: 09-2023
Publisher: Elsevier BV
Date: 09-2019
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Publisher: Elsevier BV
Date: 12-2021
Publisher: Elsevier BV
Date: 09-2023
No related grants have been discovered for Sun Wei.