PIPAL: a Large-Scale Image Quality Assessment Dataset for Perceptual Image Restoration

Understand

Image quality assessment (IQA) is the key factor for the fast development of image restoration (IR) algorithms.

• The most recent IR methods based on Generative Adversarial Networks (GANs) have achieved significant improvement in visual performance, but also presented great challenges for quantitative evaluation.
• Notably, we observe an increasing inconsistency between perceptual quality and the evaluation results.
• Then we raise two questions: (1) Can existing IQA methods objectively evaluate recent IR algorithms? (2) When focus on beating current benchmarks, are we getting better IR algorithms? To answer these questions and promote the development of IQA methods, we contribute a large-scale IQA dataset, called Perceptual Image Processing Algorithms (PIPAL) dataset.