Comments (4)
InterHand2.6M has provided optimized MANO hand model parameters. You can use render code of its repo to project mesh into image plane. Thus, groundtruth segmentation mask could be obtained.
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Thank you for the good research.
According to the paper, you said you pre-train SegFormer, but did you use only two hand images except one hand image on the Interhand 2.6M dataset?
Sure, we only use two hand images to train segFormer. The Interhand 2.6M dataset has been divided into single hand sequences and interacting hand sequence.
from hdr.
Thank you for your reply.
As far as I know, pixel-level segmentation mask images are required to train SegFormer, but the InterHand2.6M dataset basically does not provide them.
May I ask how you got it?
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Okay. Thank you for your reply.
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Related Issues (16)
- ModuleNotFoundError: No module named 'mmcv._ext' HOT 6
- Whether the pre-trained model is the model of the results in the paper HOT 4
- problem about 'load checkpoint false' HOT 2
- Hello, how do I perform a real-time test?
- demo_work_dirs file missing HOT 2
- On the issue of poor performance in replacing test images HOT 10
- training code HOT 1
- train and test code
- [Load Seg model][RuntimeError: PytorchStreamReader failed reading zip archive: invalid header or archive is corrupted] HOT 2
- Training and testing scripts HOT 1
- How to get the 2D GT for hand when I run demo.py on my own image? HOT 2
- About demo file HOT 2
- About Hand Amodal Segmentation Module HOT 1
- UnboundLocalError: local variable 'x' referenced before assignment HOT 5
- Can you open source the code for generating amodal InterHand (AIH) Dataset? HOT 1
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