AI RESEARCH
EPS: Efficient Patch Sampling for Video Overfitting in Deep Super-Resolution Model Training
arXiv CS.CV
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ArXi:2411.16312v2 Announce Type: replace Leveraging the overfitting property of deep neural networks (DNNs) is trending in video delivery systems to enhance video quality within bandwidth limits. Existing approaches transmit overfitted super-resolution (SR) model streams for low-resolution (LR) bitstreams, which are used to reconstruct high-resolution (HR) videos at the decoder. Although these approaches show promising results, the huge computational costs of