Americas, Special Report, US

[kinoteatrzarya]

We propose a new recurrent VSR network, coined Middle Recurrent Video Super-Resolution (MRVSR), based on this framework. We empirically show its competitive performance on long sequences with low motion. Figure 1: A comparison between a state-of-the-art recurrent VSR network (RLSP) and our proposed network. The former generates high frequency artifacts on long sequences with low motion. The proposed network does not. Video super-resolution (VSR) is an inverse problem that extends single-image super-resolution (SISR). While SISR aims to generate a high-resolution (HR) image from its low-resolution (LR) version, in VSR the goal is to reconstruct a sequence of HR images from the sequence of their LR counterparts. The idea behind VSR, which makes it fundamentally different from SISR, is that the fusion of several LR images produces an HR image. Therefore, VSR requires to accumulate information over a number of LR frames as large as possible. However, these iterative algorithms are relatively slow and not suitable for real-world applications. Moreover, they perform poorly when the image sequence formation model and the assumptions on motion are too simplified.




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[wangiskahn2]

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