Comments (3)
is there anyone who can explain it for me?
thanks~
from pose-residual-network-pytorch.
Same issue here. It seems to me that the evaluation part uses the ground-truth keypoints to inference the estimated keypoints. @salihkaragoz Could you explain our concerns in you evaluation code? Thanks!
from pose-residual-network-pytorch.
Hi,
We are not using the PRN for keypoint prediction but to decide on which keypoints are associated with a bounding box. So the output of PRN is there for to score each keypoint not to finetune the input keypoints. Based on these scores we run a greedy assignment method to obtain final matchings.
Thanks
from pose-residual-network-pytorch.
Related Issues (20)
- Could you give a link about keypoints estimation which you used. HOT 1
- Confuse of input and label HOT 4
- More details about the Fig.2 in your paper. HOT 1
- This repo is a scam HOT 4
- release all the code HOT 1
- help HOT 1
- Hey @VladislavZavadskyy, HOT 1
- Softmax across all keypoints? HOT 1
- Please add a licence
- Are there some wrong?
- run_webcam HOT 1
- it's just a joke
- Pre-Trained model tar archive corrupted HOT 1
- Zero division by bbox[3]
- Reproducing results reported by paper
- Corrupted tar archive HOT 2
- Licensing HOT 1
- funny work HOT 1
- question about segmentation and detection ? HOT 1
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from pose-residual-network-pytorch.