41 papers with code • 2 benchmarks • 2 datasets
Over the last decade, the process of automatic image colorization has been of significant interest for several application areas including restoration of aged or degraded images.
Let there be color!: joint end-to-end learning of global and local image priors for automatic image colorization with simultaneous classification
We present a novel technique to automatically colorize grayscale images that combines both global priors and local image features.
The system directly maps a grayscale image, along with sparse, local user "hints" to an output colorization with a Convolutional Neural Network (CNN).
In this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed.