SkipNet: Learning Dynamic Routing in Convolutional Networks
european conference on computer vision, pp. 420-436, 2018.
While deeper convolutional networks are needed to achieve maximum accuracy in visual perception tasks, for many inputs shallower networks are sufficient. We exploit this observation by learning to skip convolutional layers on a per-input basis. We introduce SkipNet, a modified residual network, that uses a gating network to selectively ...More
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