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View Code? Open in Web Editor NEWHandTailor: Towards High-Precision Monocular 3D Hand Recovery
Home Page: https://sites.google.com/view/handtailor
HandTailor: Towards High-Precision Monocular 3D Hand Recovery
Home Page: https://sites.google.com/view/handtailor
I'm trying to understand where you got common.DEPTH_RANGE
and common. DEPTH_MIN
that are used here. In your paper you specify that you scale normalized the predicted root depth when using the perspective projection. Are these values what are used to unnormalized the predicted root depth? I may have incorrectly thought that normalization had to do with the length from the root to the MCP joint (or whatever the chosen joint was), is that not the case when predicting root depth
请问能提供一下训练的参考代码吗?非常感谢
Is it possible to run app_in_the_wild.py without using a Real Sense camera? As in is it possible to simply connect the webcam of the laptop?
Hello, how to solve the installation problem of jaxlib on Windows?
as the titled said. Thanks !
ImportError: cannot import name 'cusolver' from 'jaxlib'
hi nice work!i think the neural network output predicts then using the 3D model to correct , can it be understood as a post-processing operation?
I believe this is a typo
Line 414 in 080818f
it should be
s = torch.sqrt((deltaj[0,0]**2 + deltaj[0,1]**2)/(1 - deltaj[0,2]**2))
Great work you have done with this research @LyuJ1998 . I just have a question on the joint's location converted here from uvd to xyz;
Hi, I was wondering that why we use align_idx=9, instead of root_idx 0. Is there any reason? If we will align by root before computing loss anyway, why don't we align by root in the beginning?
Hey, this is very awesome work. Will there any training code be available soon?
Hiya, I had a few questions about the tailor module
Just as a high-level overview (just to make sure I correctly understand the approach). It seems that you want to refine the predicted pose parameters from the inverse kinematics network with the insight that the 2d keypoints will generally have higher accuracy/ reliability allowing for not only a more accurate prediction but also helping with bad initializations and occlusion problems in typical optimization-based techniques face (along with fewer iterations due to a good initial condition)
I enjoyed reading your paper greatly! Thank you so much for the contribution and I look forward to your response
@lixiny I got pretty weird results, when used logitech c270 camera with it's intrisics.
I used this command,
python demo.py --fx 1078.03779 --fy 1084.50988 --cx 580.850545 --cy 245.959325
I have checked the camera matrix multiple times, and it seems okay.
Output Video link: https://drive.google.com/file/d/10oH3cL92bcvFLr1HTEfp5QOTn2WvBpVM/view?usp=sharing
As you have mentioned in the Hand Scale Optimization part.
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