Reviews: Reconstructing perceived faces from brain activations with deep adversarial neural decoding

The authors propose a brain decoding model tailored to face reconstruction from BOLD fMRI measurements of perceived faces. There are some promising aspects to this contribution, but overall in its current state there are also a number of concerning issues. Positive points: - a GAN decoder was trained on face embeddings coming from a triplet loss or identity-predicting face embedding space to output the original images. Modulo my inability to follow the deluge of GAN papers closely, this is a novel contribution in that it is the application of the existant imagenet reconstruction GAN to faces. This itself may be on the level of a workshop contribution.