  In this paper, we propose a novel architecture that iteratively discovers and
segments out the objects of a scene based on the image reconstruction quality.
Different from other approaches, our model uses an explicit localization module
that localizes objects of the scene based on the pixel-level reconstruction
qualities at each iteration, where simpler objects tend to be reconstructed
better at earlier iterations and thus are segmented out first. We show that our
localization module improves the quality of the segmentation, especially on a
challenging background.
