DegBins uses degradation-driven binning and multi-stage refinement to turn residual depth regression into a more flexible hybrid classification-regression problem that outperforms prior depth super-resolution methods on five benchmarks.
Learning complementary correlations for depth super-resolution with incomplete data in real world.IEEE Transactions on Neural Networks and Learning Systems, 35(4):5616–5626
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DegBins: Degradation-Driven Binning for Depth Super-Resolution
DegBins uses degradation-driven binning and multi-stage refinement to turn residual depth regression into a more flexible hybrid classification-regression problem that outperforms prior depth super-resolution methods on five benchmarks.