Image colorization is one of the leading-edge topics from the deep learning world. As our understanding of transfer learning and deep learning is maturing, the application scope is getting exciting and more creative. Image colorization is an active area of research and lately some exciting work has been shared by deep learning experts.
In this chapter, we learned about color theory, different color models, and color spaces. This understanding helped us reformulate the problem statement to that of mapping from a single-channel grayscale image to a two-channel output. We then worked toward building a colornet based on the works of Baldassarre and his co-authors. The implementation involved a unique three-layer network consisting of an encoder, a decoder, and a fusion layer. The fusion layer allowed us to utilize transfer learning by concatenating VGG16 embeddings with the...
