MoGe-3 Monocular 3D Geometry in ComfyUI: Metric Point Cloud, Depth Normal Maps & FOV Extraction

Deconstructing @wildmindai’s MoGe-3 monocular 3D geometry engine in ComfyUI: extracting accurate metric 3D point clouds, surface normal maps, metric depth, and optical field-of-view from any 2D image in a single inference pass.

[MOGE-3 MONOCULAR 3D GEOMETRY EXTRACTION ENGINE]

COMFYUI NODE CHAIN:
- Primary Node: MoGe-3 Metric Estimator (Open-Domain 3D Backbone)
- Secondary Output: PointCloud3D Preview + Surface Normal Generator + Depth Map Inverter
- Target Projection: Blender / Unreal Engine 5 Spatial Asset Pipeline

EXECUTION SPECIFICATION:
1. INPUT 2D FRAME LOADING:
   - Source Image: High-contrast 2D scene, architecture, or character portrait (2048x1536)

2. SINGLE-PASS METRIC DECOMPOSITION:
   - MoGe-3 extracts 3D spatial coordinates (X, Y, Z metric point cloud in world coordinates)
   - Auto-computes optical focal length and horizontal/vertical FOV angles with 98% accuracy
   - Generates 16-bit floating point Surface Normal maps for physical lighting relighting passes

3. CAMERA PROJECTION & MESH EXPORT:
   - Exports .PLY point cloud and .OBJ textured mesh with vertex color coordinates
   - Enables seamless 3D camera pan/tilt in 3D compositing software with zero parallax tearing

USE CASE MONETIZATION:
VFX match-moving, spatial photo-to-3D environment conversion, VR headset immersive parallax reproduction.

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