silence-tang/GaussianIP
[CVPR 2025] Official Implementation of GaussianIP: Identity-Preserving Realistic 3D Human Generation via Human-Centric Diffusion Prior
This project helps 3D artists and content creators quickly generate highly realistic 3D human models. You provide a text description and an image prompt, and it outputs a detailed 3D human model that faithfully preserves the identity from your image, including fine facial features and clothing details. This is for professionals who need to create custom, lifelike 3D human characters efficiently.
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Use this if you need to generate high-quality, identity-preserving 3D human models from a single image and text description, with significantly faster processing times than traditional methods.
Not ideal if you require generating non-human 3D objects or already have detailed 3D scans that just need minor adjustments.
Stars
25
Forks
1
Language
Python
License
MIT
Category
Last pushed
Aug 05, 2025
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