Transformer for Image Quality Assessment

Understand

Transformer has become the new standard method in natural language processing (NLP), and it also attracts research interests in computer vision area.

• In this paper we investigate the application of Transformer in Image Quality (TRIQ) assessment.
• Following the original Transformer encoder employed in Vision Transformer (ViT), we propose an architecture of using a shallow Transformer encoder on the top of a feature map extracted by convolution neural networks (CNN).
• Adaptive positional embedding is employed in the Transformer encoder to handle images with arbitrary resolutions.