Comments (1)
The 24 joints that the SMPL model uses do not necessarily correspond to the same joints used in various 2D datasets. As a result, we train a linear regressor that maps from the 6890 vertices of the SMPL mesh to the superset of all 2d keypoints used by various datasets (H3.6M, LSP, COCO, OpenPose, etc).
You can find the full list of keypoints here:
human_dynamics/src/datasets/video_in_the_wild_to_tfrecords.py
Lines 85 to 111 in 0887f37
from human_dynamics.
Related Issues (20)
- Where can I get the same human 3d model, that is used in this work but in fbx format?
- How to extract camera position and rotation relative to model? HOT 2
- Could it run with Camera in realtime?
- Convert predictions to world coordinates HOT 11
- conflicts pytorch version HOT 2
- Slow in rendering
- Thread confusion,leading to bad results in the demo data HOT 1
- Did you test the hmmr model on the val set or the test set of 3DPW? HOT 2
- Is commercial license available for InstaVariety dataset? HOT 2
- Size InstaVariety
- problems with testing videos HOT 2
- about the range of joints [x, y, z] HOT 1
- AttributeError: 'tuple' object has no attribute 'cpu' HOT 2
- about output parameters HOT 2
- about the unit of 2D pose parameters HOT 6
- how to use hallucinator
- Project 2d and 3d keypoints on image HOT 2
- Cannot download Instavariety videos, Request for uploading the Instavariety dataset HOT 1
- Could you provide "gt_poses.pkl" file?
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from human_dynamics.