Comments (1)
Hi, usually the separation becomes fixed at quite early iterations, so 100k is definitely enough. May I ask what configuration did you use to train the model? Also please note that due to the strong view dependency of camera/hand in this dataset, it's sometimes quite difficult for the model to perfectly tell whether the shadow is a view-dependent effect or dynamic effect without any additional priors. Hence it is expected to have some artifacts in the separation.
Hope that helps!
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Related Issues (18)
- Question about configs and skewness hyperparameters HOT 2
- Comparison to NSFF HOT 13
- Generate novel views HOT 1
- Protobuf version HOT 1
- Artifacts forming on the border of the rendered images HOT 3
- Pillow model HOT 2
- Error when training/rendering with 8 GPUs HOT 1
- How to save rendering results as ply? HOT 6
- Jax Installation HOT 3
- May I ask that there are many zip files of songs in the data directory you provided, what do they mean? If I want to train by myself, which zip files should I download?
- run python eval.py HOT 1
- How can I get the same video file as the project page after training? I only have some runtime_eval png files. Thanks HOT 3
- May I ask why there is no static background rendering in the result of using hypernerf to render the dynamic part? HOT 1
- Thank you for your work, I have a question, why does this take so long to train, or the configuration required is so high. HOT 1
- May I ask whether the dynamic Hypernerf module and the static NeRF module are optimized together, or only one optimizer is used HOT 1
- Colmap calibration. HOT 1
- Adaptivity to other dynamic datasets HOT 1
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