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Automatic Natural Image Colorization

  • Tan-Bao TranEmail author
  • Thai-Son TranEmail author
Conference paper
  • 300 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 12033)

Abstract

We introduce a technique to automatically colorize natural grayscale images that combines both local and global features. Automatic colorization is a hard problem of computer vision and usually requires user interactions such as human-labelled color scribbles or reference images to achieve proper results. Based on Convolutional Neural Networks (CNN), our model is trained in an end-to-end fashion and can process images of any resolution. We improve the model of Iizuka et al. [1] by adding edge detection network and adjusting the input of the loss function. We also compare our model with the state of the art and show some improvements. Furthermore, we try colorizing ink wash paintings and achieve a special style.

Keywords

Colorization Convolutional Neural Network Self-supervised learning 

Notes

Acknowledgements

This research was supported, in part, by Ngoc Dung Beauty Center. We thank members of Ngoc Dung AI Lab for helpful discussions and Duy-Phu Nguyen for his helpful advice.

References

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of ScienceVietnam National UniversityHo Chi Minh CityVietnam

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