Sentiment analysis aims to automatically uncover the underlying attitude that we hold
towards an entity. The aggregation of these sentiment over a population represents opinion …

Visual-semantic embedding aims to find a shared latent space where related visual and
textual instances are close to each other. Most current methods learn injective embedding …

Computer vision methods that quantify the perception of urban environment are increasingly
being used to study the relationship between a city's physical appearance and the behavior …

Research in affective computing requires ground truth data for training and benchmarking
computational models for machine-based emotion understanding. In this paper, we propose …

Social media sentiment analysis (also known as opinion mining) which aims to extract
people's opinions, attitudes and emotions from social networks has become a research …

This paper explores two new aspects of photos and human emotions. First, we show through
psychovisual studies that different people have different emotional reactions to the same …

Automatic assessment of sentiment from visual content has gained considerable attention
with the increasing tendency of expressing opinions via images and videos online. This …

There is more to images than their objective physical content: for example, advertisements
are created to persuade a viewer to take a certain action. We propose the novel problem of …

Emotion recognition in user-generated videos plays an important role in human-centered
computing. Existing methods mainly employ traditional two-stage shallow pipeline, ie …

Social media networks have become a significant aspect of people's lives, serving as a
platform for their ideas, opinions and emotions. Consequently, automated sentiment …