Memeify: A Large-Scale Meme Generation System
October 27, 2019 ยท Declared Dead ยท ๐ COMAD/CODS
"No code URL or promise found in abstract"
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Authors
Suryatej Reddy Vyalla, Vishaal Udandarao, Tanmoy Chakraborty
arXiv ID
1910.12279
Category
cs.CL: Computation & Language
Cross-listed
cs.IR
Citations
14
Venue
COMAD/CODS
Last Checked
4 months ago
Abstract
Interest in the research areas related to meme propagation and generation has been increasing rapidly in the last couple of years. Meme datasets available online are either specific to a context or contain no class information. Here, we prepare a large-scale dataset of memes with captions and class labels. The dataset consists of 1.1 million meme captions from 128 classes. We also provide reasoning for the existence of broad categories, called "themes" across the meme dataset; each theme consists of multiple meme classes. Our generation system uses a trained state-of-the-art transformer-based model for caption generation by employing an encoder-decoder architecture. We develop a web interface, called Memeify for users to generate memes of their choice, and explain in detail, the working of individual components of the system. We also perform a qualitative evaluation of the generated memes by conducting a user study. A link to the demonstration of the Memeify system is https://youtu.be/P_Tfs0X-czs.
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