Weakly Supervised RBM for Semantic Segmentation

	Weakly Supervised RBM for Semantic Segmentation
	Yong Li; Jing Liu; Yuhang Wang; Hanqing Lu; Songde Ma
	2015
会议名称	International Joint Conference on Artificial Intelligence
会议录名称	Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence
会议日期	July 25-31, 2015
会议地点	Buenos Aires, Argentina
摘要	In this paper, we propose a weakly supervised Restricted Boltzmann Machines (WRBM) approach to deal with the task of semantic segmentation with only image-level labels available. In WRBM, its hidden nodes are divided into multiple blocks, and each block corresponds to a specific label. Accordingly, semantic segmentation can be directly modeled by learning the mapping from visible layer to the hidden layer of WRBM. Specifically, based on the standard RBM, we import another two terms to make full use of image-level labels and alleviate the effect of noisy labels. First, we expect the hidden response of each superpixel is suppressed on the labels outside its parent image-level label set, and a non-image-level label suppression term is formulated to implicitly import the image-level labels as weak supervision. Second, semantic graph propagation is employed to exploit the cooccurrence between visually similar regions and labels. Besides, we deal with the problems of label imbalance and diverse backgrounds by adapting the block size to the label frequency and appending hidden response blocks corresponding to backgrounds respectively. Extensive experiments on two real-world datasets demonstrate the good performance of our approach compared with some state-of-the-art methods.
关键词	无
收录类别	EI
文献类型	会议论文
条目标识符	http://ir.ia.ac.cn/handle/173211/11766
专题	紫东太初大模型研究中心_图像与视频分析
通讯作者	Jing Liu
推荐引用方式 GB/T 7714	Yong Li,Jing Liu,Yuhang Wang,et al. Weakly Supervised RBM for Semantic Segmentation[C],2015.

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