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Deep Neural Networks for Object Detection
Christian Szegedy · Alexander Toshev · Dumitru Erhan

Sun Dec 08 02:00 PM -- 06:00 PM (PST) @ Harrah's Special Events Center, 2nd Floor #None

Deep Neural Networks (DNNs) have recently shown outstanding performance on the task of whole image classification. In this paper we go one step further and address the problem of object detection -- not only classifying but also precisely localizing objects of various classes using DNNs. We present a simple and yet powerful formulation of object detection as a regression to object masks. We define a multi-scale inference procedure which is able to produce a high-resolution object detection at a low cost by a few network applications. The approach achieves state-of-the-art performance on Pascal 2007 VOC.

Author Information

Christian Szegedy (Google)
Alexander Toshev (Google)
Dumitru Erhan (Google)

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