Colorization
Automatic and interactive image colorization using deep neural networks, with PyTorch models for ECCV 2016 and SIGGRAPH 2017 papers.
What is Colorization?
Colorful Image Colorization is an open-source implementation of deep neural networks for automatically colorizing grayscale images. It provides pre-trained models from two research papers (ECCV 2016 and SIGGRAPH 2017) that predict realistic colors, enabling applications in photo restoration, artistic enhancement, and visual effects. The project solves the problem of manual colorization by leveraging learned priors from large image datasets.
Computer vision researchers, developers working on image processing applications, and hobbyists interested in deep learning-based photo editing tools.
Developers choose this project for its production-ready, easy-to-use implementation of state-of-the-art colorization models, backed by peer-reviewed research. It offers both automatic and interactive colorization in a single package with minimal dependencies.
Overview
Automatic colorization using deep neural networks. "Colorful Image Colorization." In ECCV, 2016.
Use Cases
Best For
- Automatically colorizing historical black-and-white photographs
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