Comments (1)
The ground truth 3D keypoints we use are coming directly from the annotations of Human3.6M, where the only preprocessing we do is to subtract the pelvis joint. The 3D keypoints generated by SMPL parameters, no matter how accurate these parameters are, cannot exactly replicate the 3D keypoints that the dataset provides.
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Related Issues (20)
- How to train model with human3.6m datasets 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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