Plugin Networks for Inference under Partial Evidence

2 Jan 2019Michal KoperskiTomasz KonopczynskiRafał NowakPiotr SembereckiTomasz Trzcinski

In this paper, we propose a novel method to incorporate partial evidence in the inference of deep convolutional neural networks. Contrary to the existing, top performing methods, which either iteratively modify the input of the network or exploit external label taxonomy to take the partial evidence into account, we add separate network modules ("Plugin Networks") to the intermediate layers of a pre-trained convolutional network... (read more)

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