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Color2Embed: Fast Exemplar-Based Image Colorization using Color Embeddings by Zhao, Hengyuan; Wu, Wenhao; Liu, Yihao; He, Dongliang is a scholarly article available to read on EtoBox.

What is Color2Embed: Fast Exemplar-Based Image Colorization using Color Embeddings about?

In this paper, we present a fast exemplar-based image colorization approach using color embeddings named Color2Embed. Generally, due to the difficulty of obtaining input and ground truth image pairs, it is hard to train a exemplar-based colorization model with unsupervised and unpaired training manner. Current algorithms usually strive to achieve two procedures: i) retrieving a large number of reference images with high similarity for preparing training dataset, which is inevitably time-consuming and tedious; ii) designing complicated modules to transfer the colors of the reference image to the target image, by calculating and leveraging the deep semantic correspondence between them (e.g., non-local operation), which is computationally expensive during testing. Contrary to the previous methods, we adopt a self-augmented self-reference learning scheme, where the reference image is generated by graphical transformations from the original colorful one whereby the training can be formulated in a paired manner. Second, in order to reduce the process time, our method explicitly extracts the color embeddings and exploits a progressive style feature Transformation network, which injects th

Author

Zhao, Hengyuan; Wu, Wenhao; Liu, Yihao; He, Dongliang

Published

2021

Language

EN