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This is the rep of 'End-to-end Hand Mesh Recovery from a Monocular RGB Image'
I'm trying to build the model and is getting confused about the parameter Rs coming from the mano layer. What's the utility and meaning of Rs? Is it necessary to return from the network ?
Thanks for your excellent work!
Great work! Would you mind responding with a code snippet to run this. I have been trying to just input an image and get an output pose but its taking me a while to sift through the code.
Thanks for sharing.
Is there a pre-trained model to try and play.
I want to use it in my own dataset.
Hi @MandyMo
How can I evaluate your results? (reproducing figure6)
Hi, I'm tring to reimplement the training in the paper, but I find it very hard to get a reasonable shape result if the beta of mano isn't constraied, and the pose result is also wrong. Is there some details missing in the paper ? And may I ask when will you release the training code in the future?
As the question. And what are your environmental requirements? Thanks a lot!
Could you provide the model for hourglass for testing the performance?
model = load_hourglass(nstack = 4, pretraind_path = 'pose_model.pkl', use_bn = False).cuda()
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