Deep Neural Networks for Object Detection

Deep Neural Networks (DNNs) have recently shown outstanding performance on image classification tasks [14]. In this paper we go one step further and address the problem of object detection using DNNs, that is not only classifying but also precisely localizing objects of various classes. We present a simple and yet pow-erful formulation of object detection as a regression problem to object bounding box masks. We define a multi-scale inference procedure which is able to pro-duce high-resolution object detections at a low cost by a few network applications. State-of-the-art performance of the approach is shown on Pascal VOC. 1