Image Guided Depth Upsampling using Anisotropic Total Generalized Variation

The paper introduces a new depth image upsampling technique that tackles the low lateral resolution of modern depth cameras by formulating a convex optimization problem with higher‑order regularization. An anisotropic diffusion tensor derived from a high‑resolution intensity image guides the upsampling, and a primal‑dual algorithm is implemented for efficient, multi‑frame‑per‑second performance. Experiments on the Middlebury 2007 datasets demonstrate that this method surpasses state‑of‑the‑art approaches in both speed and accuracy, and the authors also present new datasets with precise ground truth to benchmark depth upsampling using real sensor data.

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• diffusion
• benchmarks