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In this paper, we focus on tacking the problem of weakly supervised semantic segmentation. The aim is to predict the class label of image regions under weakly supervised settings, where training images are only provided with image-level labels indicating the classes they contain. The main difficulty of weakly supervised semantic segmentation arises from the complex diversity of visual classes and the lack of supervision information for learning a multi-classes classifier. To conquer thedoi:10.1145/2733373.2806319 dblp:conf/mm/YaoHC015 fatcat:zgatbhmo6fabpirgq4x65rpdhy