Multi-View Stereo Network with Gaussian Distribution Iteration

نویسندگان

چکیده

Multi-view stereo estimates the depth maps of multiple perspective images in a scene and then fuses them to generate 3D point cloud scene, which is an essential technology reconstruction. In this paper, we propose deep learning method GDINet, applying probabilistic methods pyramid framework, can significantly improve reconstruction quality. detail, first establish Gaussian distribution for each image’s pixel iterate it framework. The mean value estimated depth, variance represents estimation error. addition, design novel loss function with excellent convergence train our network. Finally, present initialization module coarse distribution, controlling parameters reasonable range. Our results rank $2nd$ on both DTU Tanks & Temples datasets, showing that network has high accuracy, completeness, robustness. We also make visualization comparison BlendedMVS dataset (containing many aerial images) demonstrate generalization ability model.

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ژورنال

عنوان ژورنال: IEEE Access

سال: 2023

ISSN: ['2169-3536']

DOI: https://doi.org/10.1109/access.2023.3280929