Comments (1)
Hi,
The joint_loss_weight was fixed to 0.001, since the joint coordinates are in mm scale. The edge loss was important to get smooth mesh surfaces. However, initially giving the edge loss entailed trivial solutions, so we gave the loss after some training.
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Related Issues (20)
- About Train pose2mesh freihand HOT 1
- How can i get the demo input about hand?(like human_joint_input.npy) HOT 1
- Question about evaluation on 3DPW HOT 7
- How can i get the demo input about human(smpl)? HOT 4
- retrain for the upper body only HOT 1
- Question about preprocessing SURREAL. HOT 1
- Can I input a picture of my hand to create a 3D model of the shape HOT 1
- About MeshNet with 3D gt as input! HOT 7
- Estimation uncertainty problem
- visualization - 2D keypoints with input image HOT 6
- Recover joint angles from mesh HOT 2
- The input of Multiple People demo is not available HOT 2
- Multiple 3D pose from different angles as input and paint the texture to the generated model HOT 4
- Could you also release the pre-train model for meshnet HOT 1
- Queries in regards to shape parameters and results HOT 2
- Keypoints Conversion - SMPL to COCO HOT 1
- adding synthesis errors on hand joints HOT 1
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