We Are Humor Beings: Understanding and Predicting Visual Humor

12/14/2015
by   Arjun Chandrasekaran, et al.
0

Humor is an integral part of human lives. Despite being tremendously impactful, it is perhaps surprising that we do not have a detailed understanding of humor yet. As interactions between humans and AI systems increase, it is imperative that these systems are taught to understand subtleties of human expressions such as humor. In this work, we are interested in the question - what content in a scene causes it to be funny? As a first step towards understanding visual humor, we analyze the humor manifested in abstract scenes and design computational models for them. We collect two datasets of abstract scenes that facilitate the study of humor at both the scene-level and the object-level. We analyze the funny scenes and explore the different types of humor depicted in them via human studies. We model two tasks that we believe demonstrate an understanding of some aspects of visual humor. The tasks involve predicting the funniness of a scene and altering the funniness of a scene. We show that our models perform well quantitatively, and qualitatively through human studies. Our datasets are publicly available.

READ FULL TEXT

page 5

page 7

page 8

page 11

page 12

page 13

page 14

page 15

research
04/29/2021

Comparing Visual Reasoning in Humans and AI

Recent advances in natural language processing and computer vision have ...
research
10/06/2016

Searching Scenes by Abstracting Things

In this paper we propose to represent a scene as an abstraction of 'thin...
research
01/29/2016

What Can I Do Around Here? Deep Functional Scene Understanding for Cognitive Robots

For robots that have the capability to interact with the physical enviro...
research
12/10/2021

Benchmarking human visual search computational models in natural scenes: models comparison and reference datasets

Visual search is an essential part of almost any everyday human goal-dir...
research
11/11/2020

Intentonomy: a Dataset and Study towards Human Intent Understanding

An image is worth a thousand words, conveying information that goes beyo...
research
04/01/2021

Visual Attention in Imaginative Agents

We present a recurrent agent who perceives surroundings through a series...
research
07/27/2015

Discovery of Shared Semantic Spaces for Multi-Scene Video Query and Summarization

The growing rate of public space CCTV installations has generated a need...

Please sign up or login with your details

Forgot password? Click here to reset