nerfstudio-project / nerfacc

A General NeRF Acceleration Toolbox in PyTorch.
https://www.nerfacc.com/
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samples in inverse depth or Euclidean space? #142

Open cv-lab-x opened 1 year ago

cv-lab-x commented 1 year ago

hi, thanks for your great work. I have some questions about samples in nerfacc, in mipnerf360, they do uniform samples in s-space(inverse depth), and transform sample pts from s-space to t-space(Euclidean space). sdist = helper.sample_intervals( randomized, sdist, logits_resample, num_samples, single_jitter=self.single_jitter, domain=(init_s_near, init_s_far), ) tdist = s_to_t(sdist)

while in nerfacc ray_marching.cu, did you do samples in s-space or directly uniform samples in t-space(Euclidean space)?

looking forward to your reply @liruilong940607

liruilong940607 commented 1 year ago

It is directly sampled from t-space. We followed the way of sampling from NGP.