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MLGCN: An Ultra Efficient Graph Convolution Neural Model For 3D Point Cloud Analysis
To address these limitations we introduce a novel Multi-level Graph Convolution Neural (MLGCN) model, which uses Graph Neural Networks (GNN) blocks to extract features from 3D point clouds at specific locality levels.
Contour Completion using Deep Structural Priors
We introduce an iterative process that completes an incomplete image and we propose novel measures that guide this to find regions it needs to complete.
Medial Spectral Coordinates for 3D Shape Analysis
In recent years there has been a resurgence of interest in our community in the shape analysis of 3D objects represented by surface meshes, their voxelized interiors, or surface point clouds.
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