Comments (1)
Hey,
sorry for the late response.
Is it possible to do this using the trained model given in your repo?
Yes, it would be possible. You can use the UNetModel
to generate some normals, which you can then use in combination with the color images you have on your objects. But be aware that this was trained on indoor scenes, and if your objects are outside of that distribution, the predictions will be off.
But you can tackle that by creating your own dataset, with BlenderProc for example. If you need help on that open an issue in that I am a maintainer there as well. Of course you would need some realistic outputs, which you could create with the SDFGen also provided in this project.
So there are many ways of solving this.
Also, will I be required to use multiple views of the same objects for my problem?
That shouldn't be a problem, however, my approach only uses one view, so giving it more information doesn't help the end result.
Best,
Max
from singleviewreconstruction.
Related Issues (11)
- Missing color_normal_mean.hdf5 for pretrained model HOT 4
- The data file is lost! HOT 4
- Camera pose HOT 4
- confusion about the projection matrix used HOT 2
- Which data to use ? HOT 4
- How to reconstruct 3D scene from just one rgb image with pretrained model? HOT 6
- Environment installation failure HOT 2
- performance HOT 2
- Replica-dataset HOT 1
- I get an error in run_on_example_scenes_from_scenenet.py. HOT 7
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from singleviewreconstruction.