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In this paper, we proposed a framework of constructing two types of theautomatic image aesthetics assessment models with different CNN architecturesand improving the performance of the image's aesthetic score prediction by theensemble. Moreover, the attention regions of the models to the images areextracted to analyze the consistency with the subjects in the images. Theexperimental results verify that the proposed method is effective for improvingthe AS prediction. Moreover, it is found that the AS classification modelstrained on XiheAA dataset seem to learn the latent photography principles,although it can't be said that they learn the aesthetic sense.

Exploring CNN-based models for image's aesthetic score prediction with using ensemble