PhyDNet
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Code for our CVPR 2020 paper "Disentangling Physical Dynamics from Unknown Factors for UnsupervisedVideo Prediction"
When I read paper Le_Guen_Disentangling_Physical_Dynamics_CVPR_2020_supplemental.pdf for MNIST dataset there are 6 Encoder Blocks and 6 Decoder Blocks. When I read code from this repo for the MNIST dataset (the only...
Hi, I'm really interested in your paper and would like to reproduce the results on SST and Traffic BJ dataset. However, I couldn't find them because the links are dead....
After a quick read of the paper and the supplementary material I could not find anything related to boundary conditions. So question is: are there any boundary conditions in the...
Hi author, could you please disclose the setting of the teacher forcing ratio used for the human3.6 dataset? and Other training parameters (training epoch, batch_size) if you would like to...
In paper K is a function of h_tilde_t and E(u_t). In code, the implementation is 24 combined = torch.cat([x, hidden], dim=1) # concatenate along channel axis 25 combined_conv = self.convgate(combined)...
Hello, I'm trying to use this model to predict cloud movement on 256x256 images. I want to base the model on the one you used for SST but I'm not...
I successfully ran the moving mnist model and now I am also interested in running the evaluation code on the human3.6 dataset. Can this pretrained model also be made available?
Hi Authors, I ran the code using the default configuration on Moving MNIST by directly executing `python3 main.py`. The final MSE obtained after 1000 epochs is around 75.26 which is...
Hello, the paper is very interesting. I tried to run the proposed code, but got MSE 39. After that, I tried to change the Lmoment to 0.1 and 0.01, but...
The shape of data in dataset Traffic BJ is 2 channels. (shape: [B, 2, 32, 32]) The mse in Traffic BJ are the **mean** of channels or the **sum** of...