NTIRE 2021 Challenge on Video Super-Resolution

TL;DR

The NTIRE 2021 Challenge on Video Super-Resolution evaluated various methods for improving video resolution, including conventional and low frame rate scenarios, with numerous participants achieving state-of-the-art results.

Contribution

This paper presents the evaluation results and solutions from the NTIRE 2021 Video Super-Resolution Challenge, highlighting advancements in both standard and challenging low frame rate environments.

Findings

High participation with 470 total teams

State-of-the-art performance achieved in both tracks

Effective solutions for low frame rate SR environments

Abstract

Super-Resolution (SR) is a fundamental computer vision task that aims to obtain a high-resolution clean image from the given low-resolution counterpart. This paper reviews the NTIRE 2021 Challenge on Video Super-Resolution. We present evaluation results from two competition tracks as well as the proposed solutions. Track 1 aims to develop conventional video SR methods focusing on the restoration quality. Track 2 assumes a more challenging environment with lower frame rates, casting spatio-temporal SR problem. In each competition, 247 and 223 participants have registered, respectively. During the final testing phase, 14 teams competed in each track to achieve state-of-the-art performance on video SR tasks.