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amanchadha / iSeeBetter

iSeeBetter: Spatio-Temporal Video Super Resolution using Recurrent-Generative Back-Projection Networks | Python3 | PyTorch | GANs | CNNs | ResNets | RNNs | Published in Springer Journal of Computational Visual Media, September 2020, Tsinghua University Press
https://arxiv.org/abs/2006.11161
MIT License
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about the loss #16

Closed heiheihei-ops closed 3 years ago

heiheihei-ops commented 3 years ago

Hello I have noticed that, when calculated the G or the D loss, you have divided it by the data length in your code, is there any usage of this operation? Waiting for your answer, Thanks a lot! https://github.com/amanchadha/iSeeBetter/blob/b2e5326779cee8dc08eab1439ea03fd243ad3173/iSeeBetterTrain.py#L110

amanchadha commented 3 years ago

Hi @heiheihei-ops , this corresponds to the batch size as stated in equation (7) of our paper: https://arxiv.org/pdf/2006.11161.pdf