Face Sketch to Image Generation using Hybrid GAN

  • Unique Paper ID: 171761
  • Volume: 11
  • Issue: 8
  • PageNo: 1357-1361
  • Abstract:
  • Creating lifelike facial images from hand-drawn sketches is a complex task with broad applications, ranging from artistic and design purposes to criminal investigations. This paper presents an innovative web application powered by a hybrid Generative Adversarial Network (GAN) model, combining the strengths of DCGAN and Cycle-GAN for superior image synthesis. Users can seamlessly upload sketches, generate high-quality images, and download results, supported by real-time processing feedback. The architecture, featuring an intuitive interface and advanced GAN training methods, is discussed alongside evaluation metrics for image fidelity. This approach opens new avenues for digital creativity and practical use in law enforcement.

Copyright & License

Copyright © 2025 Authors retain the copyright of this article. This article is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

BibTeX

@article{171761,
        author = {Pranav Asane and Shantanu Kharade and Shubham Tapale and Neeraj Kalambe and Priti Malkhede},
        title = {Face Sketch to Image Generation using Hybrid  GAN},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {8},
        pages = {1357-1361},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=171761},
        abstract = {Creating lifelike facial images from hand-drawn sketches is a complex task with broad applications, ranging from artistic and design purposes to criminal investigations. This paper presents an innovative web application powered by a hybrid Generative Adversarial Network (GAN) model, combining the strengths of DCGAN and Cycle-GAN for superior image synthesis. Users can seamlessly upload sketches, generate high-quality images, and download results, supported by real-time processing feedback. The architecture, featuring an intuitive interface and advanced GAN training methods, is discussed alongside evaluation metrics for image fidelity. This approach opens new avenues for digital creativity and practical use in law enforcement.},
        keywords = {Sketch-to-image generation, Generative Adversarial Networks, Hybrid GANs, Image synthesis, Web- based tools.},
        month = {January},
        }

Cite This Article

  • ISSN: 2349-6002
  • Volume: 11
  • Issue: 8
  • PageNo: 1357-1361

Face Sketch to Image Generation using Hybrid GAN

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