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Depth map super-resolution is an emerging topic due to the increasing needs and applications using RGB-D sensors. Together with the color image, the corresponding range data provides additional information and makes visual analysis tasks more tractable. However, since the depth maps captured by such sensors are typically with limited resolution, it is(More)
The use of time-of-flight sensors enables the record of full-frame depth maps at video frame rate, which benefits a variety of 3D image or video processing applications. However, such depth maps are typically corrupted by noise and with limited resolution. In this paper, we present a learning-based depth map super-resolution framework by solving a MRF(More)
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