Reviews: FPNN: Field Probing Neural Networks for 3D Data

The paper introduces Field Probing Neural Networks, an extrinsic construction based on 3D volumetric fields that circumvents limitations of voxel based approaches. The paper is well written and I find the idea rather interesting, despite not having a huge gap in raw performance (but a huge one in terms of computational resources). There are many repetitions (mostly nouns) in the text which could be removed to make it easier to read. "However, existing 3D CNN pipelines" - I would remove However. Figure 1: An visualization - A visualization. I would like the authors to make clear that their construction is purely extrinsic and that therefore in case of deformable objects it will not be invariant to isometries.