Large-scale labeled training datasets have enabled deep neural networks to excel across a
wide range of benchmark vision tasks. However, in many applications, it is prohibitively …

This article reviews recent computer vision techniques used in the assessment of image
aesthetic quality. Image aesthetic assessment aims at computationally distinguishing high …

We are witnessing a novel era of creativity where anyone can create digital content via
prompt-based learning (known as prompt engineering). This article investigates prompt …

Sarcasm indicates the literal meaning is contrary to the real attitude. Considering the
popularity and complementarity of image-text data, we investigate the task of multi-modal …

Sentiment analysis of online user generated content is important for many social media
analytics tasks. Researchers have largely relied on textual sentiment analysis to develop …

We address the challenge of sentiment analysis from visual content. In contrast to existing
methods which infer sentiment or emotion directly from visual low-level features, we propose …

Humans are emotional creatures. Multiple modalities are often involved when we express
emotions, whether we do so explicitly (such as through facial expression and speech) or …

With the ever-expanding volume of visual content available, the ability to organize and
navigate such content by aesthetic preference is becoming increasingly important. While still …

Psychological research results have confirmed that people can have different emotional
reactions to different visual stimuli. Several papers have been published on the problem of …

Effective visual features are essential for computational aesthetic quality rating systems.
Existing methods used machine learning and statistical modeling techniques on handcrafted …