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We propose CornerNet, a new approach to object detection where we detect an object bounding box as a pair of keypoints, the top… Expand We present a conceptually simple, flexible, and general framework for object instance segmentation. Our approach efficiently… Expand We study the problem of attributing the prediction of a deep network to its input features, a problem previously studied by… Expand In this work, we revisit the global average pooling layer proposed in , and shed light on how it explicitly enables the… Expand We present a new dataset with the goal of advancing the state-of-the-art in object recognition by placing the question of object… Expand The use of object proposals is an effective recent approach for increasing the computational efficiency of object detection. We… Expand Deep Neural Networks (DNNs) have recently shown outstanding performance on image classification tasks . In this paper we go… Expand Thinking about intelligent robots involves consideration of how such systems can be enabled to perceive, interpret and act in… Expand We present an efficient O(n+1/?4.5-time algorithm for computing a (1+?)-approximation of the minimum-volume bounding box of n… Expand We present a data structure and an algorithm for efficient and exact interference detection amongst complex models undergoing… Expand