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:
- Dinesh N
- Lakshmanan S
- Rakshit Mishra
- 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.
Project Poster
