# Weakly-Supervised Semantic Segmentation Network With Deep Seeded Region Growing

Zilong HuangXinggang WangJiasi WangWenyu LiuJingdong Wang

This paper studies the problem of learning image semantic segmentation networks only using image-level labels as supervision, which is important since it can significantly reduce human annotation efforts. Recent state-of-the-art methods on this problem first infer the sparse and discriminative regions for each object class using a deep classification network, then train semantic a segmentation network using the discriminative regions as supervision... (read more)

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