Comments (5)
The bounding box is usually roughly estimated. For example, if you have the object mask, it is possible to run algorithm like visualhull to get the rough geometry. You can also assign a unit bounding box if you know the object's rough size.
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Thanks for your answer. My target dataset is the open scenes such as a basketball game without a fixed boundary. I wonder if these can be constrainted into such a bbox since some values are unknown and uncertain.
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It would be quite challenging to model unbounded scenes with the current version of NSVF. Since we are basically based on voxels and will prune them during training. So it currently only works in Euclidean space. For large unbounded scenes, it would very inefficient to work in such scenes. I would be interested in how it will look like.
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I've got your words. Thank you.
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It would be quite challenging to model unbounded scenes with the current version of NSVF. Since we are basically based on voxels and will prune them during training. So it currently only works in Euclidean space. For large unbounded scenes, it would very inefficient to work in such scenes. I would be interested in how it will look like.
Hello, I've read your paper recently! It's an excellent work. But I have some questions about the details. In the training stage, the voxels are pruned to get more accurate voxels. I want to know if the pruned voxel are applied int the inference stage? Look forward your apply! Thank you!
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Related Issues (20)
- stuck with arg distributed-no-spawn, strange OUT OF MEMORY message without that
- Why the validation loss is smaller than the training loss?
- Build is not working HOT 4
- question about the dynamic scene HOT 1
- Conda environment files HOT 1
- CUDA kernel failed : no kernel image is available for execution on the device in clusters. HOT 2
- Too slow training HOT 3
- How to get the correct bbox.txt intrinsic.txt ? HOT 5
- Please share training script for large objects HOT 2
- AttributeError: module 'fairnr' has no attribute 'clib' HOT 3
- Request for official results on testing set.
- Hello, it says in your code that the hypernetwork does not work, but why?And your paper shows that hypernetwork works HOT 2
- why to add a 10% bias on x? HOT 4
- How to produce datatset for training in NSVF?
- NSVF dataset convention HOT 2
- How to obtain test_traj.txt
- Why so slow for training HOT 2
- a bug in inverse_cdf_sampling_kernel HOT 1
- Wired Depth Image of Free Viewport Rendering
- Error undefined symbol when import build_octree, is there a python implementation for build_octree?
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