Weaknesses: Weaknesses: - Some masks do not look reasonable when visual cues are considered, for example, the top left mask of Figure 7, which nevertheless might make sense without the image shown. Despite the paper saying "due to the nature of our Amodal-VAE, we discard RGB pixels...", I wonder if the VAE is also able to condition on the instance appearance somehow and if it helps. It didn't surprise me much, as it makes training input more "noisy" and training more easily overfitting (to some RGB features). Humans can leverage RGB in sort of a reasoning way, i.e. when the mask can have two explanations, use RGB to match the two hypothesis via some mental simulation, and decide. This can be too hard for neural networks trained for one task.