Awesome-Image-Colorization

Why we included this project

This is a well-organized reading list for anyone researching or building deep-learning colorization systems, whether the goal is restoring old photographs, recoloring anime frames, or adding color to black-and-white video. It covers both automatic and user-guided approaches, and the user-guided section is split by interaction style: scribbles, reference images, palettes, and text prompts. That makes it easy to find the technique that matches the input model your product actually supports. The video colorization section is a genuine bonus, since keeping colors consistent across frames is a different problem from single-image colorization and the relevant papers are usually scattered across the literature. Each entry links to the paper and, where available, its code or demo, so you can go from reading to running a baseline without much hunting. For a team scoping a colorization feature, this is a practical map of the field rather than a tool you deploy.