diff --git a/README.md b/README.md
index 210af0a..671e353 100644
--- a/README.md
+++ b/README.md
@@ -5,9 +5,9 @@ Created by Hugues THOMAS
 
 ## Introduction
 
-This repository contains the implementation of **Kernel Point Convolution** (KPConv) in PyTorch. *[Work in progress]*
+This repository contains the implementation of **Kernel Point Convolution** (KPConv) in [PyTorch](https://pytorch.org/).
 
-KPConv is also available in [Tensorflow](https://github.com/HuguesTHOMAS/KPConv) (original implementation)
+KPConv is also available in [Tensorflow](https://github.com/HuguesTHOMAS/KPConv) (original but older implementation)
  
 KPConv is a point convolution operator presented in our ICCV2019 paper ([arXiv](https://arxiv.org/abs/1904.08889)). If you find our work useful in your 
 research, please consider citing:
@@ -23,14 +23,31 @@ research, please consider citing:
 
 ## Installation
 
-TODO
+This implementation has been tested on Ubuntu 18.04 and Windows 10. Details are provided in [INSTALL.md](./INSTALL.md).
+
 
 ## Experiments
 
-Currently only two experiments are available in Pytorch: classification on ModelNet40 and segmentation on S3DIS.
+We provide scripts for three experiments: ModelNet40, S3DIS and SemanticKitti. The instructions to run these 
+experiments are in the [doc](./doc) folder.
 
-TODO: Guide for runnig experiments
-TODO: More experiments
+* [Object Classification](./doc/object_classification_guide.md): Instructions to train KP-CNN on an object classification
+ task (Modelnet40).
+ 
+* [Scene Segmentation](./doc/scene_segmentation_guide.md): Instructions to train KP-FCNN on a scene segmentation 
+ task (S3DIS).
+ 
+* [SLAM Segmentation](./doc/slam_segmentation_guide.md): Instructions to train KP-FCNN on a slam segmentation 
+ task (SemanticKitti).
+ 
+* [New Dataset](./doc/new_dataset_guide.md): Instructions to train KPConv networks on your own data.
+ 
+* [Pretrained models](./doc/pretrained_models_guide.md): We provide pretrained weights and instructions to load them.
+ 
+* [Visualization scripts](./doc/visualization_guide.md): For now only one visualization script has been implemented: 
+the kernel deformations display.
+
+TODO: Guide for these experiments
 
 ## Acknowledgment
 
@@ -40,4 +57,4 @@ Our code uses the <a href="https://github.com/jlblancoc/nanoflann">nanoflann</a>
 Our code is released under MIT License (see LICENSE file for details).
 
 ## Updates
-* 31/03/2020: Initial release.
+* 27/04/2020: Initial release.