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fwd_code's Issues

Code Release

Hi @Caoang327,
Thanks for your great job! I'd like to know when will you release the code. Thanks sincerely.

The results by the code do not match the reported results

Hi, I tried to run the pre-trained model provided in the repository, but the result is worse than the results reported in the paper (PSNR: ~14, SSIM: ~0.55, LPIPS: ~0.385). The synthesized images look very similar to the pictures in the paper. So, I don't know what is the problem.

output_view_000013

Camera parameters

How were the camera parameters of the 4x downsampled DTU dataset images generated? And why aren't they used during inference? (seems like the original dtu_down4/camera.npy is used)

Bad performance when training on scale_factor 200

During training, I found that the scale_factor has a significant impact on the training results. I noticed that some other projects use a scale_factor of 200 when utilizing DTU, and I think this might represent the real scale. Therefore, I modified this parameter, but the model's performance deteriorated significantly, with the depth loss remaining above 0.8 and not decreasing. However, if I set it to default value 100, the depth loss decreases rapidly, and the model performs much better. I would like to ask if you remember this situation and if you have any suggestions on how to fix this issue.

training on resized image

Thanks for your work. I have a question about training on resized images. I want to train on DTU images of size (192,256), and I noticed that the DTU_Dataset code automatically handles the resizing for both image and intrinsics. However, when I resize the image, the PSNR drops to around 13 after 10000 steps of training. I'm unsure why this is happening, as I don't see any theoretical flaws that could result in this.

This is the result of 7000 steps for resized image
1

This is the result of 7000 steps for original size image
2

Do you have any clue why this is happening? Thank you!

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