Comments (1)
You can load both binvox models and the corresponding octree models, and then compare predicted octrees with the ground truth octrees, as done in all other experiments.
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Related Issues (20)
- Tensorflow HOT 1
- boost referencing problem HOT 3
- ogn_converter.cpp HOT 7
- Reading both .binvox and .oc for auto encoder tests HOT 4
- Inputting octrees directly HOT 1
- ogn_converter output nothing HOT 4
- "single_view_3d/Shapenet_cars/snapshot/snapshot_iter_136000.caffemodel" corresponds to pred or known network ? HOT 2
- Compilation error: "undefined reference to 'caffe::OGNConvLayer<float>...' HOT 2
- Cannot compile the code HOT 3
- Memory issue when training OGN with different data HOT 2
- Build Issue HOT 5
- Compilation was successful, but there was an error when using train_known.sh HOT 4
- About the provided Example models HOT 1
- Testing on own image HOT 3
- no field named "ogn_data_param" HOT 5
- Mapping between ####.ot and original shapenet models? HOT 1
- How to obtain 3D models of resolutions of 128^3 HOT 2
- About ogn_converter.cpp
- Message type "caffe.LayerParameter" has no field named "ogn_data_param".
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