Comments (2)
jackyjsy
commented on June 14, 2024
Hi there, OpenPose and AlphaPose are faster, but we care more about accuracy and less about speed during this CVPR challenge, especially the accuracy for hands keypoints. That's why we chose the HRNet trained on whole-body pose dataset.
As a bottom-up method, OpenPose is less accurate than most top-down methods. I haven't checked out the new version of AlphaPose yet (which includes the hands and feet keypoints). It might also be a reasonable choice if it is accurate enough.
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HW140701
commented on June 14, 2024
Thank you for your reply, and thank you for the open source code.
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Related Issues (20)
- Problem in directories provided in https://github.com/jackyjsy/CVPR21Chal-SLR/tree/main/SL-GCN HOT 1
- Conv3D for WLASL HOT 6
- Problem in sign_gendata.py HOT 3
- Running Docker Command HOT 3
- Accuracy of V2 paper HOT 2
- the SL-GCN motion-related data prediction acc very low ? HOT 1
- Images' Docker HOT 3
- CUDA capability is not compatible with the current PyTorch installation HOT 1
- Train for bone HOT 2
- No such file or directory: 'final_models/val_rgb_final.pth' HOT 1
- How to get correct 'train_val_labels.pkl' ? HOT 2
- AUTSL dataset corrupted or in unknown format HOT 4
- gen_flow.py HOT 1
- Inference time calculation
- IndexError in forward func of Conv3D/Sign_Isolated_Conv3D_clip.py
- Help from an admirer
- RuntimeError: The size of tensor a (270) must match the size of tensor b (272) at non-singleton dimension 2
- Trouble running the Docker image
- Puzzle about HHA representation generation.
- Number Parameters
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