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Update README.md

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skanti committed Mar 12, 2019
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@@ -140,7 +140,7 @@ Once you have downloaded the dataset files, you can run `./Routines/Script/Annot

### Scan and CAD Repository

In this work we used 3D scans from the [ScanNet](https://github.com/ScanNet/ScanNet) dataset and CAD models from [ShapeNet (version 2.0)](https://www.shapenet.org/). If you want to use it too, then you have to send an email and ask for the data - they usually do it very quickly.
In this work we used 3D scans from the [ScanNet](https://github.com/ScanNet/ScanNet) dataset and CAD models from [ShapeNetCore (version 2.0)](https://www.shapenet.org/). If you want to use it too, then you have to send an email and ask for the data - they usually do it very quickly.

Here is a sample (see in `./Assets/scannet-sample/` and `./Assets/shapenet-sample/`):

@@ -155,7 +155,7 @@ The data must be processed such that scans are represented as **sdf** and CADs a
In order to create **sdf** voxel grids from the scans, *volumetric fusion* is performed to fuse depth maps into a voxel grid containing the entire scene.
For the sdf grid we used a voxel resolution of `3cm` and a truncation distance of `15cm`.

In order to generate the **df** voxel grids for the CADs we used [this](https://github.com/christopherbatty/SDFGen) repo (thanks to @christopherbatty).
In order to generate the **df** voxel grids for the CADs we used a modification (see `CADVoxelization.py`) of [this](https://github.com/christopherbatty/SDFGen) repo (thanks to @christopherbatty).

### Creating Training Samples

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