First of all, thanks for sharing this amazing work!
I was wondering if you have tried more fine-grained sampling strategy, meaning lowering the granularity when defining the positive and negative samples from the ground truth, and increasing the number of samples / queries?
Currently the granularity $\sigma=0.1$ and you sample 550 points during training. I was wondering if you decrease the $\sigma$ to 0.01 or 0.001, will this create reconstruction with more details and how much more time will it cost? Thanks.
First of all, thanks for sharing this amazing work!
I was wondering if you have tried more fine-grained sampling strategy, meaning lowering the granularity when defining the positive and negative samples from the ground truth, and increasing the number of samples / queries?
Currently the granularity $\sigma=0.1$ and you sample 550 points during training. I was wondering if you decrease the $\sigma$ to 0.01 or 0.001, will this create reconstruction with more details and how much more time will it cost? Thanks.