Comments (2)
I guess the best depth results are obtained using --seq_length=3 and separately, the best pose results are obtained using --seq_length=5. I don't think you can have both in the same pipeline.
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@kristijanbartol is right. They are trained with different sequence lengths as well as splits. You could read the experimentation part of our paper for more details.
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Related Issues (20)
- Flag add_flownet not recognized by Tensorflow HOT 1
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