SMVNet: Deep Learning Architectures for Accurate and Robust Multi-View Stereopsis

Shizeng Yao,Yangyang Wang,Hadi AliAkbarpour,Guna Seetharaman,Raghuveer Rao,Kannappan Palaniappan

2020 IEEE Applied Imagery Pattern Recognition Workshop (AIPR)（2020）

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摘要

We describe Spatial Voxel-Net (SVNet) and Multi-View Voxel-Net (MVNet), a cascade of two novel deep learning architectures for calibrated multi-view stereopsis that reconstructs complicated outdoor 3D models accurately. Both networks use a sequence of RGB images based on ordered camera poses in a coarse-to-fine fashion. SVNet extracts summarized features and analyzes the spatial relationship among...

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关键词

Deep learning,Solid modeling,Three-dimensional displays,Conferences,Computer architecture,Feature extraction,Data mining

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