Reviews: Multiview Aggregation for Learning Category-Specific Shape Reconstruction

Summary: The authors address the problem of learning category-specific shape reconstruction using the proposed NOX representation. The NOX representation builds on the NOCS idea of normalized object coordinate systems which represents all instances in an object category within a unit cube. Predicting a perspective projection of the NOCS representation in the camera view (called the NOCS map) is thus equivalent to predicting the object shape coordinates in the unit cube (or NOCS). The authors extend this to not just predict NOCS coordinates of the visible surface in a camera view (first intersection of ray from pixel to object) but also coordinates of the the "last* intersection of the ray. This pair of first and last intersection maps termed NOX thus provide a reasonably complete picture of object shape (for mostly convex objects).