Four variants of the model architecture were trained on a random subset (50%) of ShapeNetCore. The models are based on two types of data augmentations: random noise perturbations (Gaussian normal) and point deletion (using uniform random sampling). The models are as follows:
| Model | noise strength (%) | points removed (%) |
|---|---|---|
| pc_denoiser_1 | 1 | 0 |
| pc_denoiser_2 | 1 | 50 |
| pc_denoiser_3 | 2 | 0 |
| pc_denoiser_4 | 2 | 50 |
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