I notice that the actual noise has more moiré patterns than traditional blue noise. But it does probably sample better over a time series.
However I agree about the visual result… Qualitatively, the GBN results look almost like WSJ illustrations, with tight, flowing patterns. In contrast, GBN looks noisier but much more organic, like film grain.
Whether the visual difference will matter depends on the application. If you're reducing grayscale to 1 bit, as in the paper's examples, you're very aware of any patterns. However if you're reducing a floating point color image to 8 bits per color channel, you may never be able to spot the difference.