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$\mathrm{F^2Depth}$: Self-supervised Indoor Monocular Depth Estimation via Optical Flow Consistency and Feature Map Synthesis
To evaluate the generalization ability of our $\mathrm{F^2Depth}$, we collect a Campus Indoor depth dataset composed of approximately 1500 points selected from 99 images in 18 scenes.
Indoor Monocular Depth Estimation
Monocular Depth Estimation
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Projective Parallel Single-Pixel Imaging: 3D Structured Light Scanning Under Global Illumination
The 4D LTC in pPSI are reduced to projection functions, thereby enabling a highly efficient data capture process.
