microsoft / microsoft/TRELLIS.2
Poor reconstruction of text / small details from image
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- Dominant language
- Python
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Description
Overall results are good for organic shapes, but I’m consistently facing issues when the input image contains text, lettering, or fine details.
The generated meshes tend to:
- Distort letters heavily
- Randomize strokes and edges
- Lose sharp corners and inner cut-outs
- Merge or deform small details beyond recognition
This happens even when the input image is clean, high-contrast, and well-lit.
Is this a known limitation of Trellis 2?
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
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Research direction
The report does not identify a source file, model component, entry point, or test to investigate. Start by reproducing the behavior with the attached image and inspect the relevant TRELLIS.2 reconstruction pipeline. Done would require confirming whether text and fine-detail distortion is a known limitation or producing a scoped fix with regression coverage.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- computer-graphics, machine-learning
- Issue type
- Bug
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100