Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment
Learning Conditional Knowledge Distillation for Degraded-Reference Image Quality Assessment
An important scenario for image quality assessment (IQA) is to evaluate image restoration (IR) algorithms. The state-of-the-art approaches adopt a full-reference paradigm that compares restored images with their corresponding pristine-quality images. However, pristine-quality images are usually unavailable in blind image restoration tasks and real-world scenarios. In this paper, we propose …