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This is nice because the original 3DGS technique initialized itself with a point cloud generated using a traditional COLMAP process https://en.wikipedia.org/wik

This is nice because the original 3DGS technique initialized itself with a point cloud generated using a traditional COLMAP process https://en.wikipedia.org/wiki/Structure_from_motion https://en.wikipedia.org/wiki/Structure_from_motion

Maken 2y ago
The original 3DGS paper relied on some really hand-wavy heuristics to optimice the gaussians' location and size (and yet it worked remarkably well).
- Etheryte 2y ago
  The value of the parameter was chosen by I picked it.
  - deleted 2y ago
    [deleted]
  - Terr_ 2y ago
    Hey guys, I think I found the NSA crypto-saboteur! :p
- eigenman 2y ago
  As someone who works in numerical optimization, this is a dirty little secret of our profession. The optimization algorithms in the literature are great at finding local minima, but often are very sensitive to the initialization as to how small the objective is. Good heuristics for initialization are thus critical for finding a good (small objective) minimizer. Sometimes this gets to the point where the local optimization algorithm does a trivial refinement of the heuristic’s solution.
jonas21 2y ago
The point cloud is a by-product of of aligning the input images. You essentially get it for free.
sorenjan 2y ago
So do this paper, although they get basically the same result from random initialization. But as mentioned, the point cloud is free since they need the camera poses anyway. > We initialize our samples either randomly or from point clouds, typically from Structure-from-Motion (SfM) as in 3DGS
- krasin 2y ago
  > But as mentioned, the point cloud is free since they need the camera poses anyway. If you have a rigid multi-camera rig, the camera poses might be known from calibration, but then the particular scene shot on such a rig, could be reconstructed without COLMAP or other structure-from-motion tools, if I understand it correctly.

Maken 2y ago

The original 3DGS paper relied on some really hand-wavy heuristics to optimice the gaussians' location and size (and yet it worked remarkably well).

Etheryte 2y ago
The value of the parameter was chosen by I picked it.
- deleted 2y ago
  [deleted]
- Terr_ 2y ago
  Hey guys, I think I found the NSA crypto-saboteur! :p
eigenman 2y ago
As someone who works in numerical optimization, this is a dirty little secret of our profession. The optimization algorithms in the literature are great at finding local minima, but often are very sensitive to the initialization as to how small the objective is. Good heuristics for initialization are thus critical for finding a good (small objective) minimizer. Sometimes this gets to the point where the local optimization algorithm does a trivial refinement of the heuristic’s solution.

jonas21 2y ago

The point cloud is a by-product of of aligning the input images. You essentially get it for free.

sorenjan 2y ago

So do this paper, although they get basically the same result from random initialization. But as mentioned, the point cloud is free since they need the camera poses anyway. > We initialize our samples either randomly or from point clouds, typically from Structure-from-Motion (SfM) as in 3DGS

krasin 2y ago
> But as mentioned, the point cloud is free since they need the camera poses anyway. If you have a rigid multi-camera rig, the camera poses might be known from calibration, but then the particular scene shot on such a rig, could be reconstructed without COLMAP or other structure-from-motion tools, if I understand it correctly.