Project title

Text to Image generation using Generative Adversarial Networks on a dataset of flower images with captions

Submitted to:

  • Dr. Vipul Mishra (Assistant Professor)
  • Tejalal Choudhary (Ph.D Scholar)

Submitted By:

  1. Dinesh N
  2. Lakshmanan S
  3. Rakshit Mishra
  4. Renish Samir Khimani

Project Description

A new implementation of generative models using adversarial nets is called as Generative Adversarial Network (GAN). It uses two networks simultaneously running together, a generator model(G) and a discriminator model (D). The former generates an image from the input (text here) and the latter is used as classifier of genuineness by comparison of generated images from G and the real images in the dataset.

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