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License: Other
🔥DM-NeRF in PyTorch (ICLR 2023)
License: Other
Hi,
I have a self-capture data like kitti style. It has a rgb image, synced point cloud, and 3D bbox label.
How to generate the training data in our data?
Hi,
can you show how to preprocess scannet scenes for training? I tried to run preprocess.py first and then split.py. It gave me train and test split, but when running train_scannet.py it says ins_rgb.hdf5 is missing. How should i get this hdf5 file?
Thank you!
Hi,
thanks for excellent work.
when run Mesh Generation:CUDA_VISIBLE_DEVICES=0 python -u test_dmsr.py --config configs/dmsr/test/meshing.txt.
“ValueError: Surface level must be within volume data range. ”will be reported
Hi,
thanks for excellent work, how can i do decomposition and reconstruction, is there any avaiiable command
Hello,
Thanks for your great work. Will you release the video of the training dataset?
Thanks
Hi! Thanks for your wonderful work.
In your paper, it says:"Note that, the recent Semantic-NeRF (Zhi et al., 2021a) is also not comparable because it only learns 3D semantic categories, not individual 3D objects."
I’m a little bit confused about why dont you directly use the instance masks to train the semantic-nerf the compare with your work?
Why we need the scene center? I don't understand.
In generate_poses_eval function, u list the mani_center:
mani_centers = {'bathroom': [0.779178, 1.05247, 0.380208], 'bedroom': [-1.29552, 1.72703, 0.2946], 'dinning': [-0.633653, 0.295162, 0.279743], 'kitchen': [-2.52579, -0.103821, 1.47165], 'reception': [0.579352, -0.099242, 0.092597], 'restroom': [-0.001277, -2.85079, 0.588084], 'office': [-0.717374, 0.929292, 0.904515], 'study': [-0.519422, -2.16509, 1.07392]}
Can u explain the manipulation matrix generater? Thanks!!
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