An Unbiased View of hitnet
An Unbiased View of hitnet
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This paper provides HITNet, a novel neural network architecture for real-time stereo matching. Opposite to quite a few new neural network ways that operate on an entire costvolume and trust in 3D convolutions, our solution does not explicitly make a volume and alternatively depends on a fast multi-resolution initialization move, differentiable 2D geometric propagation and warping mechanisms to infer disparity hypotheses. To achieve a significant level of precision, our community not simply geometrically factors about disparities but will also infers slanted airplane hypotheses making it possible for to additional correctly execute geometric warping and upsampling operations.
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