Replaces proprietary facial geometry extraction tools with a position map regression network for end-to-end 3D reconstruction. It maps 2D image pixels to 3D coordinates using a single encoder-decoder architecture without morphable model fitting.
Tech Stack
PythonAI, ML & Data
Why PRNet?
• End-to-end regression without iterative fitting
• Supports large pose facial alignment
• Provides dense 3D mesh output (68k points)
Limitations
• Requires significant GPU memory for inference
• Limited to facial geometry only
• Dependency on older TensorFlow versions
3/4/2026
Last Update
947
Forks
169
Issues
MIT
License
Financial Leak Detected
Stop the "SaaS Tax"
Your team could be burning cash. Switching to PRNet instantly boosts your runway.
