Super-resolution of interpolated downsampled semi-dense depth map

Ilya Makarov, A. Korinevskaya, Vladimir Aliev
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引用次数: 7

Abstract

We study depth map reconstruction for a specific task of fast rough depth approximation having sparse depth samples obtained from low-cost depth sensors or SLAM algorithms. We propose a model interpolating downsampled semi-dense depth values and then processing super-resolution. We study our method in comparison with the state-of-the-art approaches transferring RGB information to depth. It appears that the proposed approach can be used to approximately estimate high-resolution depth maps.
插值下采样半密集深度图的超分辨率
我们研究了基于低成本深度传感器或SLAM算法获得的稀疏深度样本的快速粗略深度近似的特定任务的深度图重建。我们提出了一种插值下采样半密集深度值然后处理超分辨率的模型。我们将该方法与最先进的将RGB信息传输到深度的方法进行了比较。结果表明,该方法可用于高分辨率深度图的近似估计。
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