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In this paper, we propose an encoder-decoder convolutional neural network (CNN) architecture for estimating camera pose (orientation and location) from a single RGBimage. The architecture has a hourglass shape consisting of a chain of convolution and up-convolution layers followed by a regression part. The up-convolution layers are introduced to preserve the fine-grained information of the input image. Following the common practice, we train our model in end-to-end manner utilizing transferdoi:10.1109/iccvw.2017.107 dblp:conf/iccvw/MelekhovYKR17 fatcat:2xh4n4dckjhazgy7kc7hdfx3fy