Style Transfer using CNN

Style Transfer using CNN

Author Name : Ashis Kamani, Laman Ansari, Suhaib Khaleel, Srikari Rallabandi, Grandhe Venkata Guna Sundhar, Sharvari Yeole, Priyanga Durairaj

ABSTRACT

Convolutional Neural Networks (CNNs) are a category of Neural Network that have proven very effective in areas such as image recognition and classification. CNNs have been successful in computer vision related problems like identifying faces, objects and traffic signs apart from powering vision in robots and self-driving cars.

CNN is shown to be able to well replicate and optimise these key steps in a unified framework and learn hierarchical representations directly from raw images. If we take a convolutional neural network that has already been trained to recognize objects within images then that network will have developed some internal independent representations of the content and style contained within a given image.

Hence This can be violated and used for style transfer.