Replace depth alpha mask logic with torch.where for gradients in splatfacto #2856
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jb-ye
reviewed
Jan 31, 2024
| @@ -779,8 +779,7 @@ def get_outputs(self, camera: Cameras) -> Dict[str, Union[torch.Tensor, List]]: | |||
| W, | |||
| background=torch.zeros(3, device=self.device), | |||
| )[..., 0:1] # type: ignore | |||
| depth_im[alpha > 0] = depth_im[alpha > 0] / alpha[alpha > 0] | |||
| depth_im[alpha == 0] = 1000 | |||
| depth_im = torch.where(alpha > 0, depth_im / alpha, depth_im.detach().max()) | |||
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Just an unrelated comment, compute the mean(depth) has very high variance in estimation. I would prefer to compute mean(1/depth) as this is more related to disparity maps across views.
ArpegorPSGH
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Jun 22, 2024
…tfacto (nerfstudio-project#2856) * replace alpha depth logic with torch.where for differentiability
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