Review for NeurIPS paper: MetaSDF: Meta-Learning Signed Distance Functions

Weaknesses: While the ideas in this paper are novel and the results promising, I have several concerns that I feel the authors should address. In the reconstruction from surface points only, auto-decoder methods such as DeepSDF naturally fail since the predicted function quickly degenerates to zero. That said, in downstream shape completion tasks, one almost certainly has access to some estimate for the surface normal, in which case auto-decoders can be used. I would like to see some kind of experiment evaluating partial shape reconstruction with surface information (see e.g. Figure 8 in DeepSDF). I think the partial shape completion experiment is important for two reasons: The first is that it shows MetaSDF in a real-world downstream task, something that is lacking in the current version of the paper.