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about main table 1 #14

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emjay73 opened this issue Apr 8, 2022 · 6 comments
Open

about main table 1 #14

emjay73 opened this issue Apr 8, 2022 · 6 comments
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help wanted Extra attention is needed

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@emjay73
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emjay73 commented Apr 8, 2022

Thank you for sharing your code.
I'm trying to reproduce the results in the main 1 table.
Now I fully trained NeRF results (not 'ours' results) and all of the values are showing slightly worse than the values in the table.
Following is the Test Set Results / Train Set Result / Result in the paper.

<style> </style>
test   psnr ssim lpips prd
nerf flower 13.628 0.2909 0.7835 nan
nerf fortress 15.618 0.4311 0.6794 nan
nerf leaves 12.734 0.1451 0.7938 nan
nerf trex 12.419 0.3743 0.6729 nan
<style> </style>
train   psnr ssim lpips prd
nerf flower 13.062 0.2887 0.8028 nan
nerf fortress 13.539 0.3868 0.7249 nan
nerf leaves 12.38599 0.143 0.819662 nan
nerf trex 12.58406 0.425573 0.692024 nan
<style> </style>
paper   psnr ssim lpips prd
nerf flower 13.8 0.302 0.716 nan
nerf fortress 16.3 0.524 0.445 nan
nerf leaves 13.01 0.18 0.687 nan
nerf trex 15.7 0.409 0.575 nan

Can I get a clue?
Also, I wonder which dataset is used for the table among train/val/test set

@jeongyw12382
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Hmm... could you share the scripts that you've run to reproduce the results?

@jeongyw12382 jeongyw12382 added the help wanted Extra attention is needed label Apr 13, 2022
@emjay73
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emjay73 commented Apr 14, 2022

I have not changed the script from the original one.
Actually, the branch that I used is the default 'custom' branch.
Could it be the reason?
Or any version subtleties?

@jeongyw12382
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Hmm... I reported the result using codes in the main branch.
Based on my memory, there is no difference between the custom and main branch while running the base code.
I'll check the script and code tommorow and soon notice you the reason for this issue.

@jeongyw12382
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Sorry for being late.
I'm currently preparing for another conference and the dew is coming.
I will recheck this issue after my submission is completed.

@alex04072000
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Hi, I encountered the same issue of NaN when training with custom branch without COLMAP poses. Did you solve the problem?

@alien19
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alien19 commented Mar 15, 2023

@alex04072000 Have you solved it?

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