3d-cv-labeling-2026
3D Computer Vision Labeling Expert (2026)
Expert guidance on 3D annotation tools, AI-assisted labeling workflows, and training architectures for LiDAR/point cloud computer vision in autonomous vehicles, robotics, infrastructure inspection, and geospatial applications.
When to Use This Skill
✅ Use for:
- Selecting 3D point cloud annotation tools (BasicAI, Supervisely, Segments.ai, Deepen AI)
- Implementing SAM4D/Point-SAM for auto-labeling workflows
- Designing human-in-the-loop annotation pipelines
- Sensor fusion annotation (camera + LiDAR + radar)
- Training architecture decisions: specialized models vs VLMs
- Vertical-specific 3D detection (autonomous driving, inspection, agriculture, wildfire)
❌ NOT for:
- 2D image labeling without 3D context (use clip-aware-embeddings or Label Studio docs)
- General ML model training (use ml-engineer)
- Video annotation without point clouds (use computer-vision-pipeline)
- VLM prompt engineering (use prompt-engineer)
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