autonomousvision / convolutional_occupancy_networks

[ECCV'20] Convolutional Occupancy Networks
https://pengsongyou.github.io/conv_onet
MIT License
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No noise in input point clouds? #30

Closed raphaelsulzer closed 3 years ago

raphaelsulzer commented 3 years ago

Hi,

thank you very much for making this great work available here.

I was experimenting with retraining your network for which I downloaded the preprocessed ShapeNet and synthetic room dataset. You state in the paper that you "sample 3000 points from the mesh and apply Gaussian noise with zero mean and standard deviation 0.05" to generate noisy input point clouds. (I understand the reasoning in this issue, and can see in the config files that it is actually 0.005.)

However, to me it seems like there is no added noise in neither the pointcloud.ply nor pointcloud.npz files in both the ShapeNet and synthetic room dataset. If I follow your approach correctly these files are generated with the sample_mesh.ply script from the occupancy networks repository. In the export_points function for generating occupancy samples noise is added, however not in the export_pointcloud function, which is used as reconstruction input. Shouldn't this be the case, since you postulate to reconstruct meshes from noisy point clouds?

Kind regards

pengsongyou commented 3 years ago

Hi @raphaelsulzer ,

Thanks for your interest in our work!

We don't add noise directly to our GT data. Instead, we add noises during the data loading process. Please refer to the code here and here.

Hope this resolves your question.

Best, Songyou

raphaelsulzer commented 3 years ago

Yes, that makes it clear. Thank you!