An Extensive Survey on Sketch to Photo Synthesis Methods: Trends and Challenges

Authors

  • Jyoti S. Raghatwan Research Scholar, SKN College of Engineering,Pune, Asst.Prof., RMD Sinhgad School of Engineering
  • Sandhya Arora Professor, Cummins college of Engineering, Pune

Keywords:

Deep learning, Face sketch, Model driven, Data-driven

Abstract

Nowadays Face sketch- photo synthesis has drawn the attention of many researchers. Since the Photo to sketch synthesis or sketch to photo synthesis is used in many different application, detailed review is very much important to analyse state-of-the-art approaches. With this in mind, we offer a thorough analysis of the existing deep learning-based and traditional approaches, which fall into the categories of data-driven and model-driven approaches, in this study. A comparative study of the evaluated methods is conducted by considering several factors like the performance measurements, algorithms, and dataset.

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Published

29.01.2024

How to Cite

Raghatwan, J. S. ., & Arora, S. . (2024). An Extensive Survey on Sketch to Photo Synthesis Methods: Trends and Challenges. International Journal of Intelligent Systems and Applications in Engineering, 12(13s), 711 –. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/4656

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Research Article