jitengmu / a-sdf Goto Github PK
View Code? Open in Web Editor NEWA-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation (ICCV 2021)
License: MIT License
A-SDF: Learning Disentangled Signed Distance Functions for Articulated Shape Representation (ICCV 2021)
License: MIT License
Hi, thanks for sharing the great work.
Could you explain what's the difference between the generation and interpolation in the code? And which table in the paper are they correspond to if I compute the metrics by eval.py. Thanks
Hi, thanks for sharing this great work!
My current work is comparing with A-SDF as a baseline, and I'm wondering if we can get the texture or color of the 3D models? Thanks!
rbo_laptop_release_test.zip
https://nextcloud.nautilus.optiputer.net/s/Ecr6ZHokBStAgST)/s/Ecr6ZHokBStAgST
returns : empty response
Hi, @JitengMu , thank you very much for your great work. I am trying to replicate your work. Although you have already released your datasets, I am still interested in the process of your data. You have mentioned in the Data Generation section that we should use Manifold to create watertight meshes. I am interested in the code you use to generate Manifold Obj Files.
I tried using:
./manifold source_path target_path
But the result of mine are different from your datasets. It seems to be smoother in your data. Could you tell me the commands you used in the Manifold step?
Looking forward to your reply.
Hi! I was trying to download data and pretrained model as mentioned on readme.md via
https://nextcloud.nrp-nautilus.io/s/Ecr6ZHokBStAgST
But says this site can't be reached. Can you update the link for download?
Thanks in advance!
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