View Proposal

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Proposer

Idris Ibrahim

Title

Sketch to Real using GAN (Generative Adversarial Network)

Goal

The aim of the project is to develop a Generative Adversarial Network (GAN)-based model for sketch-to-image generation. The primary goal is to create a system that takes hand-drawn sketches as input from users and converts them into realistic images.

Description

Sketch to Real using GAN is a form of image-to-image translation task where the objective is to generate realistic images from sketches or line drawings. Generative Adversarial Networks (GANs) have demonstrated significant success in this domain and are widely utilised for such purposes. The transformation of sketches into realistic images using GANs falls within the realm of image-to-image translation, with the aim of creating lifelike images from initial sketches or line drawings. GANs, celebrated for their effectiveness in this area, employ a distinctive adversarial training framework involving a generator and discriminator. The generator produces synthetic images, and the discriminator evaluates them for realism. This dynamic interplay facilitates the creation of high-quality, realistic images from simple sketches, exemplifying the power and versatility of GANs in tasks related to visual content generation.

Resources

Look at the Url >> Proposed Projects 2023-24 >>Project (5)

Background

Well-Developed Programming, image procession, vision, research Skills

Url

External Link

Difficulty Level

Challenging

Ethical Approval

Full

Number Of Students

1

Supervisor

Idris Ibrahim

Keywords

image-to-image translation, sketch to real, generative adversarial etworks (gans), realistic image generation, lifelike images, adversarial training, generator, discriminator, synthetic images, realism evaluation, dynamic interplay, visual content generation.

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Computing (2 Years)
Master of Science in Software Engineering
Bachelor of Science in Computing Science