Comments (2)
Here is the answer to your first question: there is a class called no_ref_back_projection
in Burst De-noising/Network.py
that performs the cyclic burst sampling in the forward pass. It uses torch.roll
to shift the burst and then reshape both the original and shifted versions to couple the frames and finally concatenate the results.
from burstormer.
from burstormer.
Related Issues (10)
- Do you plan to release your source codes and model weights? HOT 5
- Question for pre-trained weights link. HOT 5
- Download link of the pre-trained weights is wrong. It is BIPNet pre-trained model link. HOT 1
- Question for training time HOT 7
- Ask for results of other model's visualization results
- Can't reproduce the result for BurstSR dataset(Track2) HOT 7
- Question for training of Burst De-noising.(loss function, data generation and training tricks) HOT 5
- What is the purpose of the BFF module in the network.
- Regarding Batchsize
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from burstormer.