Closed HLinChen closed 5 months ago
Same, I gain a PSNR of 35.15 when validating on dtu_scan24 which surpasses the reported value 30.64 a large margin.
Hi @HLinChen and @hbai98
We do not separate the training/test images when reporting PSNR. As mentioned in the paper, we use PSNR as a metric to assess the capacity to overfit the input images and capture details. I hope this helps!
Hi @mli0603,
If you do not separate the training/test images for PSNR, then why are the reported PSNR scores so much lower than those obtained by the model when overfitting to all training views? I'm trying to compare to your approach, but it's unclear to me exactly how the PSNR reported in the paper were computed.
Thanks!
From your codes, I find you use all images for training on both tnt and dtu datasets. So what are the test images? Can you provide the indices of test images?