Comments (8)
I used initial learning rate as 1e-5!
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For all stages, I used 1e-5.
from dinet.
Hi thanks for sharing the tips!
May I know the learning rate you used eventually? I guess many people including myself have limited computation to tune it multiple times. It would be greatly helpful if you can share it!
Thank you
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Thank you for your quick reply!
Sorry but did you use 1e-5 only for clip or for every stage of frame training?
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Thanks for sharing that!
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Did you train SyncNet from scratch or use the provided pre-trained model? Also, I thought SyncNet only had a clip mode, but in your above response, it seems like there is a frame mode mentioned.
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Similar to dinet training code that author provided, I trained syncnet from scratch.
For frame stage, audio feature should be deepspeech featrue from [n-2:n+3], if we use n th frame as face feature.
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Hello, I also have a question. How can we determine whether the model has converged during the training process of DINet?
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Related Issues (20)
- License HOT 3
- Generated output mouth is not moving. HOT 4
- 使用universome的HDTF数据集复现
- 关于论文的补充材料
- Lips are not driven when using custom videos. HOT 2
- Landmark detection for what?
- The fps of generated video
- 12G GPU train Error?? HOT 1
- Am I missing a file? HOT 1
- Loss convergence损失收敛问题
- 请问trans_conv网络中用了11和7的卷积核是做什么考虑 HOT 2
- File "inference.py", line 59, in <module> raise ('video frames are misaligned with detected l HOT 3
- My own data, the effect is very poor, come with a mask, this is why HOT 6
- Pre-trained model error HOT 1
- RuntimeError: Found no NVIDIA driver on your system. HOT 2
- Openface problem "detected landmarks" HOT 6
- For money, who can show how to train a model in DiNet? HOT 11
- Error- "Our method cannot handle videos with large change of facial size!!" HOT 8
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