VIP: Finding Important People in Images

TL;DR

This paper introduces a method to automatically determine the importance of individuals in group photos using visual cues, improving image captioning and related applications.

Contribution

It proposes a new importance measure for people in images and demonstrates its effectiveness in predicting importance and enhancing image captioning tasks.

Findings

Automatically predicting importance improves captioning accuracy

Importance correlates with visual saliency but is not identical

Incorporating importance enhances image description applications

Abstract

People preserve memories of events such as birthdays, weddings, or vacations by capturing photos, often depicting groups of people. Invariably, some individuals in the image are more important than others given the context of the event. This paper analyzes the concept of the importance of individuals in group photographs. We address two specific questions -- Given an image, who are the most important individuals in it? Given multiple images of a person, which image depicts the person in the most important role? We introduce a measure of importance of people in images and investigate the correlation between importance and visual saliency. We find that not only can we automatically predict the importance of people from purely visual cues, incorporating this predicted importance results in significant improvement in applications such as im2text (generating sentences that describe images of groups of people).