Project title

Image to Image Translation using GAN

Submitted to:

  • Dr. Madhushi Verma (Assistant Professor)
  • Dr. Vipul Mishra (Assistant Professor)
  • Rajiv Ranjan

Submitted By:

  1. Shanmukha Sai Sumanth Yenneti
  2. Anshuman Agarwal
  3. Sonali Mehta
  4. Sree Raaggavan.S
  5. Ashok Babu.B

Project Description

Many problems in image processing, and computer vision can be viewed as translating an input image into a corresponding output image. Just as a concept may be expressed in English, a scene may be condensed as an RGB image, a gradient field, an edge map, a semantic label map, etc. In analogy to automatic language translation, we define automatic image-to-image translation as the task of translating one possible representation of a scene into another, given enough training data. Here we explore GANs in the conditional setting. Just as GANs learn a generative model of data, conditional GANs (cGANs) learn a conditional generative model. This makes cGANs suitable for image-to-image translation tasks, where we condition on an input image and generate a corresponding output image.

Project Poster

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