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Code release for "Memory In Memory: A Predictive Neural Network for Learning Higher-Order Non-Stationarity from Spatiotemporal Dynamics" (CVPR 2019)

Python 99.09% Shell 0.91%
cvpr-2019 predictive-neural-network video-prediction spatiotemporal-dynamics

mim's Issues

Visualise results

Hi,
Thank you for the work. I have a question about TaxiBJ dataset. How do you visualise results? When I save the prediction, it's grayscale.
Please advise.

Thank you!

Commands to train?

Hi, nice paper. For the github, could you please provide the training commands that you used?

求教几个小问题

大佬些,我看到论文中预测的帧存在结果比较模糊的问题,请问是否考虑过类似RNN+GAN的模型来预测生成更清晰的未来帧?

关于基线数据集,除了移动MNIST,以及低像素的Human3.6M,是否尝试过更高分辨率的图像?

另,README.md中的图片挂了.

About the taxibj dataset?

Hello, I want to know that the channel of taxibj dataset is 2. How to calculate the ssim between the predict frames and input frames?

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