Hello, first of all thanks for your very interesting work.
I'm trying to train a very simple custom scene, but the PSNR remains low even after many iterations on the Vanilla NeRF.
The Lego data set has a mean PSNR of 16 on the test set after only 500 iterations, while mine has a mean PSNR of 12 after 10k iterations.
I generated my dataset with BlenderProc using the same poses of the Lego dataset, and I checked that the intrinsics, bbox and poses are taken correctly.
These are two images of the train set:
And these are the results after 10k iterations on the test set:
And if I try to render images of the train set the results are slightly better, but still not acceptable.
I can see during the training that the Loss is decreasing and the PSNR is increasing but not as fast as it did with the Lego data set, and they are oscillating a lot.
Do you have any suggestion to fix this behavior?
Thanks a lot!
Hello, first of all thanks for your very interesting work.
I'm trying to train a very simple custom scene, but the PSNR remains low even after many iterations on the Vanilla NeRF. The Lego data set has a mean PSNR of 16 on the test set after only 500 iterations, while mine has a mean PSNR of 12 after 10k iterations. I generated my dataset with BlenderProc using the same poses of the Lego dataset, and I checked that the intrinsics, bbox and poses are taken correctly.
These are two images of the train set:
And these are the results after 10k iterations on the test set:
And if I try to render images of the train set the results are slightly better, but still not acceptable.
I can see during the training that the Loss is decreasing and the PSNR is increasing but not as fast as it did with the Lego data set, and they are oscillating a lot.
Do you have any suggestion to fix this behavior? Thanks a lot!