Computational image aesthetic evaluation is a computable human aesthetic perception and
judgment realized by machines, which has a significant impact on a variety of applications …

Challenges in image aesthetics assessment (IAA) arise from that images of different themes
correspond to different evaluation criteria, and learning aesthetics directly from images while …

Deep learning approaches for Image Aesthetics Assessment (IAA) have shown promising
results in recent years, but the internal mechanisms of these models remain unclear …

Quality assessment, which evaluates the visual quality level of multimedia experiences, has
garnered significant attention from researchers and has evolved substantially through …

In this work, we point out that the major dilemma of image aesthetics assessment (IAA)
comes from the abstract nature of aesthetic labels. That is, a vast variety of distinct contents …

We present a comprehensive study on a new task named image color aesthetics
assessment (ICAA), which aims to assess color aesthetics based on human perception …

Is aesthetic impact different from beauty? Is visual salience a reflection of its capacity for
effective communication? We present Impressions, a novel dataset through which to …

Image aesthetics assessment (IAA) aims at predicting the aesthetic quality of images.
Recently, large pre-trained vision-language models, like CLIP, have shown impressive …

Vision-language foundation models have had considerable increase in performances in the
last few years. However, there is still a lack of comprehensive evaluation methods able to …

Computational inference of aesthetics is an ill-defined task due to its subjective nature. Many
datasets have been proposed to tackle the problem by providing pairs of images and …