Researchers are exploring various methods for evaluating and enhancing digital image quality, including the use of multi-scale aesthetic features and graph convolutional neural networks. Other approaches being investigated involve generative adversarial networks, graph neural networks, and image segmentation, among others. The applications of these methods appear to be diverse, ranging from image enhancement and restoration to art evaluation and style transfer.