Forgot README and gitmodules.

.gitmodules

@@ -1,9 +1,6 @@
 [submodule "code/daml-shape-completion"]
 	path = code/daml-shape-completion
 	url = https://github.com/davidstutz/daml-shape-completion
-[submodule "code/shape-completion-benchmark"]
-	path = code/shape-completion-benchmark
-	url = https://github.com/davidstutz/shape-completion-benchmark
 [submodule "code/bpy-visualization-utils"]
 	path = code/bpy-visualization-utils
 	url = https://github.com/davidstutz/bpy-visualization-utils

README.md

@@ -1,5 +1,10 @@
 # Learning 3D Shape Completion from Laser Scan Data with Weak Supervision
 
+**Note: An updated and improved version of this approach is available as
+[pre-print](https://arxiv.org/abs/1805.07290) on ArXiv
+and the corresponding repository is
+[davidstutz/arxiv2018-improved-shape-completion](https://github.com/davidstutz/arxiv2018-improved-shape-completion).**
+
 This repository contains paper and code corresponding to:
 
 D. Stutz, A. Geiger. **Learning 3D Shape Completion from Laser Scan Data with Weak Supervision.** IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2018.
@@ -14,9 +19,24 @@ Please cite as:
       year = {2018}
     }
 
+
 Also check the [project page](http://davidstutz.de/projects/shape-completion/)
 for the final publication, code and data.
 
-![AML.](screenshot.png?raw=true "AML.")
+Here, you can find:
+
+* `paper/`: the LaTeX source of the final paper.
+* `code/`:
+    * [davidstutz/daml-shape-completion](https://github.com/davidstutz/daml-shape-completion),
+      Torch and C++ implementation of the proposed approach and baselines as well
+      as the created benchmarks.
+    * [davidstutz/mesh-evaluation](https://github.com/davidstutz/mesh-evaluation),
+      C++ implementation of mesh-to-mesh / mesh-to-point distance
+      used for evaluation.
+    * [davidstutz/bpy-visualization-utils](https://github.com/davidstutz/bpy-visualization-utils),
+      Python and Blender (`bpy`) utilities for visualization as shown below.
+    * [davidstutz/mesh-voxelization](https://github.com/davidstutz/mesh-voxelization),
+      C++ implementation of mesh voxelization for computing occupancy grids
+      and signed distance functions from watertight meshes.
 
-See `code/README.md` for details and license of the code.
+![AML.](screenshot.png?raw=true "AML.")