Comments (1)
Hi, thanks for your interest. Yes, it works for moving cameras and you can export everything you mentioned by running our algorithm. But in case of dynamic cameras, our rendered background is not that compelling compared to videos with static cameras. You can refer to the Fig.16 of our supplementary document to see more examples of our background rendering.
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Related Issues (20)
- Why is SMPL pose condition zeroed out before 20 epochs and every 20 epochs after that ? HOT 1
- I can see the vis result using aitviewer, but have OSError: [Errno 32] Broken pipe. when i want to export the video. HOT 2
- Is PyTorch3D compatible with the other libraries versions? HOT 2
- SynWild dataset inaccurate body poses HOT 4
- Setting up training dataset HOT 3
- About pre trained sdf field HOT 3
- About the function transform_smpl HOT 1
- batch_size: 2 error HOT 2
- textured mesh
- how to get correct miltiview rendering result in one frame HOT 1
- Model checkpoints, training data, and evaluation code
- error in training HOT 1
- Poor results on PeopleSnapshot dataset HOT 1
- train.py not running HOT 2
- Canonical Texture
- Pretrain
- Demo Frame Skip HOT 1
- train.py : ImportError: libtorch_cuda_cu.so: cannot open shared object file: No such file or directory HOT 3
- ImportError: libcudart.so.10.1: cannot open shared object file: No such file or directory
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