Researchers have developed a human-in-the-loop pipeline for segmenting 3D assets into a 2D parameterized atlas. This method utilizes SAM 2 and Label Studio for interactive segmentation of rendered views, which are then back-projected onto the model's UV parameterization. The resulting atlas aids in downstream tasks like material assignment and semantic labeling, with evaluations showing its utility across various geometries. AI
IMPACT This human-in-the-loop approach could streamline 3D content creation workflows by automating segmentation tasks.
RANK_REASON The cluster contains a research paper published on arXiv detailing a new method for 3D asset segmentation.
- arXiv
- CORE Recommender
- Hugging Face
- Label Studio
- SAM 2
- Saptarshi Neil Sinha
- alphaXiv
- CatalyzeX
- DagsHub
- Gotit.pub
- ScienceCast
AI-generated summary · Google Gemini · from 2 sources. How we write summaries →