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Exploring Real-Time Super-Resolution: Benchmarking and Fine-Tuning for Streaming Content

Evgeney Bogatyrev
Khaled Abud
Ivan Molodetskikh
Nikita Alutis
Dmitry Vatolin
Main:10 Pages
17 Figures
Bibliography:4 Pages
16 Tables
Appendix:11 Pages
Abstract

Recent advancements in real-time super-resolution have enabled higher-quality video streaming, yet existing methods struggle with the unique challenges of compressed video content. Commonly used datasets do not accurately reflect the characteristics of streaming media, limiting the relevance of current benchmarks. To address this gap, we introduce a comprehensive dataset - StreamSR - sourced from YouTube, covering a wide range of video genres and resolutions representative of real-world streaming scenarios. We benchmark 11 state-of-the-art real-time super-resolution models to evaluate their performance for the streaming use-case.

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