Abstract:With the help of the space-to-depth and depth-to-space modules, we provide a convolutional neural network design for depth estimation. We show designs that down sample the spatial information of the picture utilizing space-to-depth (SD) as opposed to the widely used pooling methods (Max-pooling and Average-pooling). The space-to-depth module may shrink the image while maintaining the spatial information of the image in the form of additional depth information. This technique is far superior to Max-pooling, whi… Show more
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