Reviews: Integrated perception with recurrent multi-task neural networks

This paper is crystal clear and the main points are easily accessible. The key idea of integrated learning of representation sharing and output correlation is sound and well executed in the new architecture comprising CNNs, R-CNNs, RNNs and autoencoders. My main concern is regarding the experimental evaluation. There is clear room for improvement: (1) the authors are encouraged to use the standard VOC 2012 dataset instead of the more obsolete VOC 2010/2007 datasets--this makes direct comparison of different methods possible; (2) the baseline methods (Independent and Multi-task in Table 1) are too simple to justify the effectiveness of the proposed method, and more recent work on multi-task deep learning should be compared. Note that, although this paper contrasts itself clearly from the literature, it does not mean that it is enough to evaluate the proposed method only against simple baselines.