Neural Joking Machine : Humorous image captioning
Abstract
What is an effective expression that draws laughter from human beings? In the present paper, in order to consider this question from an academic standpoint, we generate an image caption that draws a "laugh" by a computer. A system that outputs funny captions based on the image caption proposed in the computer vision field is constructed. Moreover, we also propose the Funny Score, which flexibly gives weights according to an evaluation database. The Funny Score more effectively brings out "laughter" to optimize a model. In addition, we build a self-collected BoketeDB, which contains a theme (image) and funny caption (text) posted on "Bokete", which is an image Ogiri website. In an experiment, we use BoketeDB to verify the effectiveness of the proposed method by comparing the results obtained using the proposed method and those obtained using MS COCO Pre-trained CNN+LSTM, which is the baseline and idiot created by humans. We refer to the proposed method, which uses the BoketeDB pre-trained model, as the Neural Joking Machine (NJM).
Cite
@article{arxiv.1805.11850,
title = {Neural Joking Machine : Humorous image captioning},
author = {Kota Yoshida and Munetaka Minoguchi and Kenichiro Wani and Akio Nakamura and Hirokatsu Kataoka},
journal= {arXiv preprint arXiv:1805.11850},
year = {2018}
}
Comments
Accepted to CVPR 2018 Language & Vision Workshop