Neural Style Transfer with Pytorch - An Example of Transfer learning

This video is about neural style transfer using Neural Networks.
Here deep learning techniques are used to compose one image in the style of another image . This is known as neural style transfer and the technique is outlined in A Neural Algorithm of Artistic Style (Gatys et al.).

This video demonstrates the original style-transfer algorithm. It optimizes the image content to a particular style. Modern approaches train a model to generate the stylized image directly (similar to cyclegan).

Neural style transfer is an optimization technique used to take two images—a content image and a style reference image (such as an artwork by a famous painter)—and blend them together so the output image looks like the content image, but “painted” in the style of the style reference image.

This is implemented by optimizing the output image to match the content statistics of the content image and the style statistics of the style reference image. These statistics are extracted from the images using a convolutional network.

[kunaljain]

Very Informative. Tip - The background music is not necessary.