How does NeuralHaircut overcome the "noisy orientations map" problem in real-world data? about neuralhaircut

[Vanessik]

Hi @07hyx06! You are right!

Orientations obtained using Gabor filters are very noisy and undirected. Furthermore, 2D orientation maps provide only information on how hair looks on the surface and have no idea of how hair behaves inside the volume.
To deal with this problem, we use diffusion-based prior that was trained on synthetic hairstyles. This way, we could produce realistic hair geometry inside the volume as well as resolve the problem with proper orientations.

Ideally, having a large dataset with synthetic 3D strand-based hairstyles could resolve all problems. Unfortunately, today there are just several publicly available datasets with very simple hairstyles, that сomplicates the reconstruction of highly curly hair.

[07hyx06]

Got it, thanks!