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In order to meet the increasing need for high-quality synthetic data in computer vision applications, this study presents SynthVision, a flexible framework. With the help of a variety of assessment methods and Generative Adversarial Networks (GANs), SynthVision provides a reliable method for creating synthetic data in a variety of disciplines. We demonstrate the framework’s effectiveness in generating synthetic data that closely resembles real-world settings through thorough experimentation and analysis, therefore advancing computer vision research and application.

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SynthVision: A Comprehensive Framework for Generating High-Quality Synthetic Image Data

  • 会议论文

  • 发表日期：

    2026年

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  • Yuvraj Mehta,
  • V. Madhusudanan Pillai,
  • Udaya Unnikrishnan

摘要

In order to meet the increasing need for high-quality synthetic data in computer vision applications, this study presents SynthVision, a flexible framework. With the help of a variety of assessment methods and Generative Adversarial Networks (GANs), SynthVision provides a reliable method for creating synthetic data in a variety of disciplines. We demonstrate the framework’s effectiveness in generating synthetic data that closely resembles real-world settings through thorough experimentation and analysis, therefore advancing computer vision research and application.