NTIRE 2021 Challenge on Quality Enhancement of Compressed Video: Methods and Results

The NTIRE challenge on video quality enhancement, using the LDV dataset, evaluates methods across three tracks focused on fidelity and perceptual quality improvements of HEVC and x265 compressed videos.

Open

Year: 2021
Venue: arXiv 2021
ArXiv: arxiv.org/abs/2104.10781
URL: arxiv.org/abs/2104.10781v6
Authors: 72
Hosting: Abstract onlyARXIV-DEFAULT

Cite

Notes

Only stored in your browser.

Attribution

Abstract & full text: arxiv.org/abs/2104.10781v6ARXIV-DEFAULT
TL;DR: Semantic Scholar

Attribution policy →

Abstract

This paper reviews the first NTIRE challenge on quality enhancement of compressed video, with a focus on the proposed methods and results. In this challenge, the new Large-scale Diverse Video (LDV) dataset is employed. The challenge has three tracks. Tracks 1 and 2 aim at enhancing the videos compressed by HEVC at a fixed QP, while Track 3 is designed for enhancing the videos compressed by x265 at a fixed bit-rate. Besides, the quality enhancement of Tracks 1 and 3 targets at improving the fidelity (PSNR), and Track 2 targets at enhancing the perceptual quality. The three tracks totally attract 482 registrations. In the test phase, 12 teams, 8 teams and 11 teams submitted the final results of Tracks 1, 2 and 3, respectively. The proposed methods and solutions gauge the state-of-the-art of video quality enhancement. The homepage of the challenge: https://github.com/RenYang-home/NTIRE21_VEnh