Skip to content
New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

How to optimize EmerNeRF #21

Open
nevergone123 opened this issue Apr 4, 2024 · 1 comment
Open

How to optimize EmerNeRF #21

nevergone123 opened this issue Apr 4, 2024 · 1 comment

Comments

@nevergone123
Copy link

frame_019

Thanks for your wonderful works!

I'm doing a project related to AD simulation.
I ran emernerf on scene in which ego car move at a medium or high speed, like waymo scene id 2.
But the decomposition result is not good.

Following the approach of DynIBAR, I tried to improve emernerf by adding 2D optical flow supervision to the training process.
I merged the flow loss into the total pixel loss.
However, the flow loss did not converge during training, and the overall training results became worse.

So the questions are:

  1. How can I optimize emernerf? For example, improve its decomposition ability.
  2. If I use additional 2D optical flow supervision, besides merging the flow loss into the total_pixel_loss, what else should I do? Will this approach improve the decomposition results?

Looking forward to your advice. Thank you once again!

@ntaquan0125
Copy link

ntaquan0125 commented May 7, 2024

I think outliers come from lighting variations between views. And 2D flow supervision for fast ego-motion data should be handled with care.

Sign up for free to join this conversation on GitHub. Already have an account? Sign in to comment
Labels
None yet
Projects
None yet
Development

No branches or pull requests

2 participants