Enhancing artistic style transfer: integrating cyclegan, diffusion models, and neural painting for monet-inspired image generation

HIGHLIGHTS

• What: This project explores various approaches to style transfer specifically focusing on transforming natural images into the iconic style of Claude Monet`s paintings. The analysis provides insights into the strengths and limitations of each method and identifies areas for future improvement in reproducing Monet`s iconic style. The survey aimed to assess the aesthetic appeal, naturalness, and adherence to Monet`s style of the generated images. The aim of the survey was to gauge public perception regarding the effectiveness of deep learning models in artistically reinterpreting landscape photographs into the distinctive style of Claude Monet`s . . .
  

   

  

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