@@ -9,7 +9,7 @@ This document attempts to give a few tips.
...
@@ -9,7 +9,7 @@ This document attempts to give a few tips.
A good rule of thumb is that if your NeRF model does not seem to be converging after 20 seconds or so, it is unlikely to get much better after a long training time.
A good rule of thumb is that if your NeRF model does not seem to be converging after 20 seconds or so, it is unlikely to get much better after a long training time.
We therefore recommend adjusting the data to get clear results in the early stages of training.
We therefore recommend adjusting the data to get clear results in the early stages of training.
For large real world scenes, it is possible to get a little bit of extra sharpness by training for a few minutes at most.
For large real world scenes, it is possible to get a little bit of extra sharpness by training for a few minutes at most.
Almost all of the convergence happens in the first few seconds.
Almost all the convergence happens in the first few seconds.
The most common issue with datasets is an incorrect scale or offset in the camera positions; more details below.
The most common issue with datasets is an incorrect scale or offset in the camera positions; more details below.
The next most common issue is too few images, or images with inaccurate camera parameters (for example, if COLMAP fails).
The next most common issue is too few images, or images with inaccurate camera parameters (for example, if COLMAP fails).
