DeMoN: Depth and Motion Network for Learning Monocular Stereo
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چکیده
Our network is a chain of encoder-decoder networks. Figures 12 and 13 explain the details of the two encoderdecoders used in the bootstrap and iterative net part. Fig. 14 gives implementation details for the refinement net. The encoder-decoders for the bootstrap and iterative net use additional inputs which come from previous predictions. Some of these inputs, like warped images or depth from optical flow, need to be generated with special layers, which we describe here.
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DeMoN: Depth and Motion Network for Learning Monocular Stereo
Our network is a chain of encoder-decoder networks. Figures 15 and 16 explain the details of the two encoderdecoders used in the bootstrap and iterative net part. Fig. 17 gives implementation details for the refinement net. The encoder-decoders for the bootstrap and iterative net use additional inputs which come from previous predictions. Some of these inputs, like warped images or depth from o...
متن کاملDeMoN: Depth and Motion Network for Learning Monocular Stereo
Our network is a chain of encoder-decoder networks. Figures 15 and 16 explain the details of the two encoderdecoders used in the bootstrap and iterative net part. Fig. 17 gives implementation details for the refinement net. The encoder-decoders for the bootstrap and iterative net use additional inputs which come from previous predictions. Some of these inputs, like warped images or depth from o...
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