论文标题
NTIRE 2022挑战感知图像质量评估
NTIRE 2022 Challenge on Perceptual Image Quality Assessment
论文作者
论文摘要
本文报告了NTIRE 2022关于感知图像质量评估（IQA）的挑战，并与CVPR 2022的图像恢复和增强研讨会（NTIRE）研讨会的新趋势结合在一起。这项挑战是通过感知图像图像处理Algorithms持续解决IQA挑战的挑战。这些算法的输出图像与传统扭曲具有完全不同的特征，并且包含在此挑战中使用的PIPAL数据集中。这个挑战分为两条曲目，一个类似于以前的NTIRE IQA挑战的全参考IQA轨道，以及一个重点介绍No-Reference IQA方法的新曲目。挑战有192和179名注册参与者的两条曲目。在最后的测试阶段，有7和8个参与的团队提交了模型和事实表。与现有的IQA方法相比，几乎所有这些都取得了更好的结果，并且获胜方法可以证明最先进的性能。
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.
