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To\ntackle these two problems, we propose a Discriminative Feature Network (DFN),\nwhich contains two sub-networks: Smooth Network and Border Network.\nSpecifically, to handle the intra-class inconsistency problem, we specially\ndesign a Smooth Network with Channel Attention Block and global average pooling\nto select the more discriminative features. Furthermore, we propose a Border\nNetwork to make the bilateral features of boundary distinguishable with deep\nsemantic boundary supervision. 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