• Implemented Neural Style Transfer techniques to create visually compelling images by merging the content of one image with arbitrary artistic style of another.
• Developed a Multi-level stylization approach using a pre-trained encoder-decoder architecture based on VGG19.
• Incorporated feature transformation with alpha as the style weight parameter to precisely control the stylistic transfer effects.
• Leveraged powerful techniques such as Adaptive Instance Normalization (AdaIN) and Whitening and Coloring transforms (WCT) within the feature transformation process for image reconstruction network.

• To deploy this project run the following file : 3Adain-2WCT.ipynb
• Make sure the content Image , Style Image and Output Image paths are clearly mentioned in the notebook.

• Example 1

• Example 2

• Example 3

Below are some research papers which have been instrumental in doing this project :

• Neural Style Transfer: A Review
• Arbitrary Style Transfer in Real-time with Adaptive Instance Normalization
• Universal Style Transfer via Feature Transforms
• A Neural Algorithm of Artistic Style

If you found value in this project, please give it a star! Your support is greatly appreciated.