NTIRE 2021 Challenge on Image Deblurring

TL;DR

The NTIRE 2021 Challenge on Image Deblurring focused on recovering high-quality images from blurry, artifact-laden inputs, showcasing state-of-the-art solutions through competitive tracks involving low-resolution and JPEG-compressed images.

Contribution

This challenge report introduces two new tracks addressing joint artifacts in image deblurring, with detailed evaluation results and winning methods demonstrating advanced performance.

Findings

Winning methods achieve state-of-the-art deblurring performance.

High participation indicates strong community interest.

Effective solutions handle joint artifacts in low-res and compressed images.

Abstract

Motion blur is a common photography artifact in dynamic environments that typically comes jointly with the other types of degradation. This paper reviews the NTIRE 2021 Challenge on Image Deblurring. In this challenge report, we describe the challenge specifics and the evaluation results from the 2 competition tracks with the proposed solutions. While both the tracks aim to recover a high-quality clean image from a blurry image, different artifacts are jointly involved. In track 1, the blurry images are in a low resolution while track 2 images are compressed in JPEG format. In each competition, there were 338 and 238 registered participants and in the final testing phase, 18 and 17 teams competed. The winning methods demonstrate the state-of-the-art performance on the image deblurring task with the jointly combined artifacts.