Unlike in our setup, in theirs, images for the same concept are used both for training and to derive visual attributes (our setup is "zero-shot" at the concept level, i.e., we predict attributes of concepts not seen in training).
despite the fact that they used presumably less accurate pre-CNN visual features, the setup is much easier for them, and we take their performance to be an upper bound on ours.