Deep Unsupervised Saliency Detection: A Multiple Noisy Labeling Perspective

CVPR 2018 Jing ZhangTong ZhangYuchao DaiMehrtash HarandiRichard Hartley

The success of current deep saliency detection methods heavily depends on the availability of large-scale supervision in the form of per-pixel labeling. Such supervision, while labor-intensive and not always possible, tends to hinder the generalization ability of the learned models... (read more)

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