Mengyuan Yan

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3D shape models are becoming widely available and easier to capture, making available 3D information crucial for progress in object classification. Current state-of-theart methods rely on CNNs to address this problem. Recently, we witness two types of CNNs being developed: CNNs based upon volumetric representations versus CNNs based upon multi-view(More)
Training for Our Volumetric CNNs To produce occupancy grids from meshes, the faces of a mesh are subdivided until the length of the longest edge is within a single voxel; then all voxels that intersect with a face are marked as occupied. For 3D resolution 10,30 and 60 we generate voxelizations with central regions 10, 24, 54 and padding 0, 3, 3(More)
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