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facebookresearch / xR-EgoPose

New egocentric synthetic dataset for egocentric 3D human pose estimation
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Question about ground truth heatmap & embedding size #5

Closed diskhkme closed 4 years ago

diskhkme commented 4 years ago

Hi. First of all, thank you for sharing your great work.

I have two questions about your proposed method described in paper.

  1. In Eq (1), L_2D is calculated as mean square error between heatmaps. But how could one can get ground truth heatmap? As far as I understand, heatmaps are the probability-encoded data for joints, and usually it is a byproduct(?) of pose estimation.

I think you may assume for instance normal distribution around ground truth 3D joints and project it to generate ground truth heatmap. And I guess your approach is similar as I described, since you mentioned in the paper "... the 3D lifting module can be trained independently using 3D mocap data and its projected heatmaps." (p.7732, 5.Architecture second paragraph)

I wonder If my guess is right and whether is it okay to use fixed size(standard deviation) to generate ground truth heatmaps.

  1. Did you conduct a comparative study on embeddings dimension? I think it's quite small(20D).

    I wonder if it has serious impact on performance and/or inference speed if I change the dimension of embeddings.

DenisTome commented 4 years ago

This is going to be closed as not related to the repository