Access to sparse structure encoder/reversing decoding process
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- Python
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Description
The TRELLIS paper mentions a simple VAE is used to convert the sparse structure coordinates into a compressed format. However, are there any specs on the specific auto encoder architecture used to achieve this?
It'd be useful to know how the coordinates are encoded for the purpose of modifying the sparse structure before continuing to run more iterations within the transformer.
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
Start with the TRELLIS paper's description of the simple VAE and trace how sparse structure coordinates are compressed and reversed before further transformer iterations. Done means documenting the autoencoder architecture and encoding/decoding representation well enough for someone to modify the sparse structure and continue processing.
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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