Image Time Machine: AI-Powered Transformation of Contemporary into Historical Photographs

  • Felix Rader

    Student thesis: Master's Thesis

    Abstract

    This research introduces a tool that utilizes artificial intelligence to transform modern
    photographs into authentic representations of historical aesthetics. The tool integrates
    advanced AI technologies, including Large Language Models (LLMs), Stable Diffusion
    XL, ControlNet, and decade-specific Low-Rank Adaptation (LoRA) models, combined
    with automated prompt engineering. The objective is to capture the unique visual characteristics of different eras, mimicking the imperfections of analog and vintage photography.
    LoRA models are trained on historical images to enhance the authenticity of generated photographs. The resulting images were evaluated in a user study, which confirmed
    that the LoRA models significantly improve the quality, realism, and historical accuracy compared to images generated without them. Future enhancements may involve
    refining LoRA models and expanding to more historical periods. This research uniquely
    intersects AI, photography, and historical aesthetics, offering new ways to experience
    the present through AI-generated vintage imagery.
    Date of Award2024
    Original languageEnglish (American)
    SupervisorDavid Christian Schedl (Supervisor)

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