Comments (3)
The joints used in Human3.6M have a slightly different definition than those used by the SMPL body model, so we use a different regressor to accurately recover them from vertices during evaluation.
You can use this definition of joints during training as well, but for simplicity we use a single regressor that is compatible with all training datasets.
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Thanks! I have tried to apply both regressors on T mesh and found the joints position are slightly different as you said. It seems that the joints of Human3.6M are more near the skin than the SMPL joints, which located inside the body. Is this consistent with your observation?
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Yes, there are only minor differences.
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Related Issues (20)
- How to train model with human3.6m datasets HOT 1
- Preprocess of ground truth keypoints_3d on Human3.6M HOT 1
- question when I read the code HOT 1
- questions about "mesh_downsampling.npz" HOT 1
- Regarding fully connected baseline HOT 4
- Compute 'A', 'D', 'U' matrices HOT 6
- How to get 3d joints from demo.py and visualize it HOT 3
- About the SMPLParamRegressor
- Praise from a newbie HOT 1
- Why do you use different focal length for training and inference?
- Running βdemo.py' can't get good results HOT 2
- The problem of camera parameter βscβ HOT 1
- Loading Resnet50 pretrained?
- Asking for the weight of losses
- how to retrain this model in a new dataset with the real SMPL model
- preprocess datasets of h36m.py
- run demo.py
- wrong mesh volume
- The additional files could not be obtained.
- Pretrained model HOT 1
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