[michrassena]

This is one of the few colorizing algorithms that I've seen which creates desirable output. The images really do look like old colorized images. I wonder how the authors dealt with the differences in spectral sensitivity of their source material. There's clearly some orthochromatic plates or film being used. The image of the Seneca native 1908 is a good example. Notice how dark the field is on the patch on her skirt. With orthochromatic emulsions, the patch could have been either black or red since the emulsion isn't sensitive to red. It's most sensitive to blue, which is part of the reason skies look so white in old photos.

[citnaj]

Author here. Easy to answer that one- altering the training photos with random lighting/contrast changes (yet keeping the color targets the same) really helped to deal with varying qualities of photos. But also neural networks are just particular good at picking up on context, so that has a lot to do with why the results are so robust.