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Pytorch code for "BSRT: Improving Burst Super-Resolution with Swin Transformer and Flow-Guided Deformable Alignment", CVPRW, 1st place in NTIRE 2022 BurstSR Challenge (real-world track).

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请问作者,从代码看,你们训练用的验证集和测试用的测试集是同一个,这样测试集就是已经见过的数据,其测试结果如何能证明模型真实的泛化能力呢?

作者您好,请问您有没有试过只在Real data上训练呢?结果怎么样?是否会出现过拟合的现象?

Dear author, first and foremost thank you very much for your great work and your great effort towards improving burst super-resolution. I am currently myself training and testing your model...

Dear author, I see you set the value of offset in 10*tanh(offset), what the difference between original offset and [-10,10] offset? It seems that the magnitude is a super parameter,...

flows_list = [flow.view(b, n, 2, h // (2 ** (i)), w // (2 ** (i))) for flow, i in zip(flows, range(3))] RuntimeError: shape '[4, 7, 2, 64, 64]' is invalid...

输入必须是 batch,14,4, Height, Width,否则会报错: `RuntimeError: Given groups=1, weight of size [60, 896, 1, 1], expected input[1, 512, 160, 160] to have 896 channels, but got 512 channels instead` 请问怎么修改,比如我要输入8张raw序列,谢谢

code/synthetic/bsrt/data_processing/camera_pipeline.py line140: blue = image[:, 2, 0::2, 1::2] => blue = image[:, 2, 1::2, 0::2] ?

Excuse me, how to download the dataset which named real-world dataset in your paper? Thank you.