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Any particular reason why training with LPIPS loss? #82

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jotix16 opened this issue Dec 9, 2024 · 0 comments

jotix16 commented Dec 9, 2024 •

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Thank you for the nice work :)

I was unable to extract the reason why the LPIPS loss is used during training.

It clearly makes sense with regard to the evaluation pipeline (i.e. directly optimize what you are evaluating for).

Could you tell whether LPIPS is necessary? Is it motivated empirically or just used?

Why not use the default loss ( l1-loss + l_ssim) that is used in the 3DGS seminal work?

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