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Dynamic Zoom-in Network for Fast Object Detection in Large Images
2018
2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition
We introduce a generic framework that reduces the computational cost of object detection while retaining accuracy for scenarios where objects with varied sizes appear in high resolution images. Detection progresses in a coarse-to-fine manner, first on a down-sampled version of the image and then on a sequence of higher resolution regions identified as likely to improve the detection accuracy. Built upon reinforcement learning, our approach consists of a model (Rnet) that uses coarse detection
doi:10.1109/cvpr.2018.00724
dblp:conf/cvpr/GaoY0MD18
fatcat:wuajjprxjjfvrnczrbick6iuxi