license.txt

Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks

Copyright (c) 2018 Yizhak Ben-Shabat, Michael Lindenbaum, Anath Fischer at Technion IIT

This code is based on the following paper : Nesti-Net: Normal Estimation for Unstructured 3D Point Clouds using Convolutional Neural Networks, Yizhak Ben-Shabat, Michael Lindenbaum, Anath Fischer arXiv preprint arXiv:1812.00709.
Please cite this work if you use our software.

The code in this repository is for demo purposes only.
Individuals or academic institutes are free to use the code and trained models or train their own models as long as they acknowledge its use.
Commercial licensing is managed by the Technion Industry Liaison Office. Please contact Yizhak Ben-Shabat for details.

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.