ITM Web Conf.
Volume 40, 2021International Conference on Automation, Computing and Communication 2021 (ICACC-2021)
|Number of page(s)||5|
|Published online||09 August 2021|
Successive Image Generation from a Single Sentence
Dwarkadas J. Sanghvi College of Engineering, Mumbai, India
Through various examples in history such as the early man’s carving on caves, dependence on diagrammatic representations, the immense popularity of comic books we have seen that vision has a higher reach in communication than written words. In this paper, we analyse and propose a new task of transfer of information from text to image synthesis. Through this paper we aim to generate a story from a single sentence and convert our generated story into a sequence of images. We plan to use state of the art technology to implement this task. With the advent of Generative Adversarial Networks text to image synthesis have found a new awakening. We plan to take this task a step further, in order to automate the entire process. Our system generates a multi-lined story given a single sentence using a deep neural network. This story is then fed into our networks of multiple stage GANs inorder to produce a photorealistic image sequence.
Key words: Deep Learning / Generative Adversarial Networks / Natural Language Processing / Computer Vision / LSTM / CNN / RNN / GRU / GPT-2
© The Authors, published by EDP Sciences, 2021
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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