Action-Decision Networks for Visual Tracking With Deep Reinforcement Learning

CVPR 2017 Sangdoo YunJongwon ChoiYoungjoon YooKimin YunJin Young Choi

This paper proposes a novel tracker which is controlled by sequentially pursuing actions learned by deep reinforcement learning. In contrast to the existing trackers using deep networks, the proposed tracker is designed to achieve a light computation as well as satisfactory tracking accuracy in both location and scale... (read more)

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