From the abstract: "We evaluate our algorithm using a “colorization Turing test”, asking human subjects to choose between a generated and ground truth color ima

From the abstract: "We evaluate our algorithm using a “colorization Turing test”, asking human subjects to choose between a generated and ground truth color image." And later in the article: "However, the results from these and other past attempts tend to look desaturated. One explanation is that [1,2] use loss functions that encourage conservative predictions. [...] We instead utilize a loss tailored to the colorization problem. As pointed out by [3], color prediction is inherently multimodal – many objects, such as a shirt, can plausibly be colored one of several distinct values." This suggests that adversarial training might be a good fit. It transforms the goal from "reproduce the original colors", which is in general impossible, to "produce as convincing a colorization as possible", which is the real goal.