We present a new approach for large-scale multi-view stereo matching, which is designed to operate on ultra high-resolution image sets and efficiently compute dense 3D point clouds. We show that, using a robust descriptor for matching purposes and high-resolution images, we can skip the computa...
此外,作为patch match stereo方法的一个关键部分,视点的选择在很大程度上取决于两个图像patch之间稳定的视觉相似度量。然而,测量低纹理区域的视觉相似性总是具有挑战性的。如图2(b)所示,低纹理区域的低分辨率导致了视觉相似度的模糊性,这进一步降低了patch匹配立体方法的性能。然而,我们观察到,对于低纹理区域,尽管图2...
We present a new approach for large-scale multi-view stereo matching, which is designed to operate on ultra high-resolution image sets and efficiently compute dense 3D point clouds. We show that, using a robust descriptor for matching purposes and high-resolution images, we can skip the ...
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BlendedMVS is a large-scale MVS dataset for generalized multi-view stereo networks. The dataset contains 17k MVS training samples covering a variety of 113 scenes, including architectures, sculptures and small objects. Upgrade to BlendedMVG BlendedMVG, a superset of BlendedMVS, is a multi-purpose ...
In the framework of a robust VIO method (Hesch et al., 2013) and a fast volumetric integration technique (Klingensmith et al., 2015), this is enabled by simple and fast plane sweeping for depth estimation, followed by Acknowledgments The research leading to these results has received funding ...