This does seem to reduce to one-shot learning, but face dissimilarity metrics won't work well to describe similarity between unstructured objects like the authors propose.

Faces have a limited set of common features that are readily separable, quantifiable, and comparable, which is why face recognition can be done rather well just using a SVM. When the set of common features falls to zero, as in this paper, a face-specific net architecture will not do one-shot recognition across independent faceted objects nearly as well.