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First provide a summary of the paper, and then address the following criteria: Quality, clarity, originality and significance. The paper presents a new recursive neural network architecture for semantic scene labeling and shows that it outperforms previous approaches on two standard datasets in terms of pixel accuracy. The paper is generally very well written and the proposed model seems quite natural and conceptually clean compared to its main competitors. My only major concern is that the paper doesn't separately evaluate the effects of the combiner and decombiner networks. An even simpler model could use the combiner network to recursively collapse everything to a single root node (as is done already) but then directly feed the output of the F_sem network along with the root node F_com features into each corresponding F_lab network.