Blind image quality assessment via learnable attention-based pooling

Jie Gu, Gaofeng Meng, Shiming Xiang, Chunhong Pan

Abstract: Highlights•We propose an attention-based pooling network for BIQA.•A correlation constraint between the estimated local quality and attention weight in the network is introduced to regulate the training.•An effective and interpretable attention model can be learned merely from subjective quality scores, without accessing to attention/saliency supervision.•The learned attention-based pooling can be applied to other IQA metrics to help improve the performance.