AI turns infrared images taken in total darkness into full colour

to spot correlations between the way objects appeared in infrared and their colour in the visible spectrum. Once trained, this AI could predict the visible colouring from pure infrared images, even those originally taken in total darkness.

Browne believes the approach could become extremely accurate over time, although the results are already difficult to distinguish from genuine colour images. “I think this technology could be used for precise colour evaluation if the amount and variety of data used to train the neural network is sufficiently large to increase accuracy,” he says.

“Human faces are, of course, a very constrained group of objects, if you like. It doesn’t immediately translate to colouring a general scene,” he says. “As it stands at the moment, if you apply the method trained on faces to another scene, it probably wouldn’t work, it probably wouldn’t do anything sensible.”

Hilton also says that the same AI trained to colourise images of fruit from infrared images alone would always be fooled by a random blue banana, for instance, as it would have learned context from training data that included multiple images of yellow bananas.

Um, duh?

And not a single sample image in the entire article

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