How to encode existing 3D models (mesh or gaussian splat)?
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- Dominant language
- Python
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Description
I see that the only usage documentation provided by the readme uses an image as the input. However, this VAE architecture should be able to accept a diverse set of inputs, since the inputs to the VAE were voxelized features from a 3D model during training stage.
I want to know how we can encode existing 3D models (mesh or gaussian splat) to the embedding space using the trellis library.
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Research direction
Start with the README's image-input example and review the TRELLIS library's VAE and voxelized-feature workflow. Determine whether existing mesh or Gaussian-splat inputs are supported, then document a reproducible encoding path or clearly identify the missing capability. No specific files or tests are named in the issue.
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Assessment
- Tech stack
- python
- Domain
- computer-graphics, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100