Comments (1)
For the MNIST dataset, you can merge the 'valid'(2000 sequences) and 'test'(3000 sequences) to get 5000 sequences for evaluation. Our results are based on the 'test' set.
For the KTH dataset, I think it is maybe because of the data augmentation. Anyway, you can totally follow this code base. We will give more details in the revision.
from predrnn-pytorch.
Related Issues (20)
- The traffic4cast model
- Inconsistent dataset of Moving_MNIST in the paper and code? HOT 1
- Whether the Moving_MNIST dataset volume in PredRNN++ is the same as the code repo? HOT 3
- What's the validation dataset for KTH_action, TaxiBJ, and Human3.6M? HOT 2
- Prediction images don't change. HOT 4
- Random output images HOT 2
- misconfigured parameter `num_action_ch` for `action_cond_predrnn_v2` HOT 2
- when i use CIKM_predrnn.py ,it run wrong HOT 1
- Guidance for custom dataset HOT 1
- Pretrained model-Unexpected key HOT 1
- Generate a new Moving-MNIST dataset HOT 1
- Generate new Mnist dataset HOT 3
- Radar echo dataset HOT 3
- FileNotFoundError: [Errno 2] No such file or directory HOT 2
- radar echo dataset HOT 1
- Kth dataset: inf error HOT 2
- link of pretrained models from Tsinghua Cloud need to update
- A list of dependencies
- Problem with hidden layers HOT 1
- Why is MSE calculated with "sum" instead of "mean"? HOT 1
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from predrnn-pytorch.