Abstract: Highlights•Improving restoration performances of pre-trained VSR networks by leveraging test LR video frames.•Allowing large scale factors for test-time adaptive SR.•Showing flexibility in ways to distill knowledge.•Removing undesirable initial artifacts across video frames.•Consistently elevating performances on various VSR networks and datasets.
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