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Lately stereo matching has become a key aspect in autonomous driving, providing highly accurate solutions at relatively low cost. Top approaches on state of the art benchmarks rely on learning mechanisms such as convolutional neural networks (ConvNets) to boost matching accuracy. We propose a new real-time stereo reconstruction method that uses a ConvNet for semantically segmenting the driving scene...
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