NTIRE 2022 Challenge on Perceptual Image Quality Assessment
This addresses the problem of accurately assessing image quality for emerging perceptual processing algorithms, which is incremental as it builds on previous NTIRE challenges.
The paper tackled the challenge of perceptual image quality assessment for images processed by modern algorithms, using the PIPAL dataset, and reported that almost all participating teams achieved better results than existing methods, with the winning method demonstrating state-of-the-art performance.
This paper reports on the NTIRE 2022 challenge on perceptual image quality assessment (IQA), held in conjunction with the New Trends in Image Restoration and Enhancement workshop (NTIRE) workshop at CVPR 2022. This challenge is held to address the emerging challenge of IQA by perceptual image processing algorithms. The output images of these algorithms have completely different characteristics from traditional distortions and are included in the PIPAL dataset used in this challenge. This challenge is divided into two tracks, a full-reference IQA track similar to the previous NTIRE IQA challenge and a new track that focuses on the no-reference IQA methods. The challenge has 192 and 179 registered participants for two tracks. In the final testing stage, 7 and 8 participating teams submitted their models and fact sheets. Almost all of them have achieved better results than existing IQA methods, and the winning method can demonstrate state-of-the-art performance.