70,441 research outputs found
Automatic Understanding of Image and Video Advertisements
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 automatic advertisement understanding. To enable
research on this problem, we create two datasets: an image dataset of 64,832
image ads, and a video dataset of 3,477 ads. Our data contains rich annotations
encompassing the topic and sentiment of the ads, questions and answers
describing what actions the viewer is prompted to take and the reasoning that
the ad presents to persuade the viewer ("What should I do according to this ad,
and why should I do it?"), and symbolic references ads make (e.g. a dove
symbolizes peace). We also analyze the most common persuasive strategies ads
use, and the capabilities that computer vision systems should have to
understand these strategies. We present baseline classification results for
several prediction tasks, including automatically answering questions about the
messages of the ads.Comment: To appear in CVPR 2017; data available on
http://cs.pitt.edu/~kovashka/ad
UR-FUNNY: A Multimodal Language Dataset for Understanding Humor
Humor is a unique and creative communicative behavior displayed during social
interactions. It is produced in a multimodal manner, through the usage of words
(text), gestures (vision) and prosodic cues (acoustic). Understanding humor
from these three modalities falls within boundaries of multimodal language; a
recent research trend in natural language processing that models natural
language as it happens in face-to-face communication. Although humor detection
is an established research area in NLP, in a multimodal context it is an
understudied area. This paper presents a diverse multimodal dataset, called
UR-FUNNY, to open the door to understanding multimodal language used in
expressing humor. The dataset and accompanying studies, present a framework in
multimodal humor detection for the natural language processing community.
UR-FUNNY is publicly available for research
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