Comments (1)
The action-conditioned model is described in Appendix B.3 of the paper:
...the video prediction model is now also conditioned on a sequence of actions
a_0:T−1
, in addition to the initial frames. The generator network is modified to take an actiona_t
at each timestep, by concatenating the action to the inputs of all the convolutional layers of the main network
i.e. the robot's state is also used to condition the video prediction, not just raw video.
from video_prediction.
Related Issues (20)
- Is downloading dataset necessary for sample prediction videos? HOT 1
- Error in downloading dataset (partially downloaded) HOT 1
- Checkpoint data loss error when evaluating
- Training stability & progress HOT 1
- train with my own dataset
- FailedPreconditionError while trying to predict using gan_only model on KTH
- ValueError: as_list() is not defined on an unknown TensorShape. HOT 6
- Unable to download pretrained model HOT 1
- Using trained model for custom sized images HOT 1
- Questions about evaluation with the deterministic model
- KeyError: 'gen_states' when run train.py
- KL Loss Weight is zero
- The KHT dataset have not existed any more
- File "scripts/generate.py", line 15, in <module> from video_prediction import datasets, models ModuleNotFoundError: No module named 'video_prediction' HOT 1
- Training error HOT 4
- Testing on custom images
- Dependency Nightmare
- bash download pre-trained model gives an error
- CDNA Masks
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from video_prediction.