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Extract latent representation information? #20

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chuanenlin opened this issue Dec 25, 2019 · 3 comments
Closed

Extract latent representation information? #20

chuanenlin opened this issue Dec 25, 2019 · 3 comments

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@chuanenlin
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chuanenlin commented Dec 25, 2019

From Fig. 9, 10, 11 of the paper, I saw that clustering visualizes the latent spaces distributions (view, skeleton, motion).
I am wondering if it is possible to output the latent space data (e.g., camera-view angle in degrees of the subject for a specific frame)?

@ChrisWu1997
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Hi, there are functions to visualize latent codes in cluster.py. You can look into that code for your own need.

@chuanenlin
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Thanks for the reply.

I tried running python cluster.py -n view to test and received the following error:
line 126, in get_cluster_data all_data = torch.stack(all_data, dim=0) RuntimeError: expected a non-empty list of Tensors

Does this mean I first need to download the Mixamo dataset as described in mixamo_download_script.java, and if so, may I ask where should the .fbx files be saved and are there any specific formatting (e.g., of directory names) required?

@ChrisWu1997
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Yes, you miss the data. But there is no need to download the original fbx, we provide processed data for direct usage.

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