HaiyuWu/Vec2Face
This is the official implementation of "Vec2Face: Scaling Face Dataset Generation with Loosely Constrained Vectors", which is accepted at ICLR2025.
This project helps researchers and developers in facial recognition to quickly generate large, diverse datasets of face images. By taking an identity's unique "feature vector" (a mathematical representation of their face), it can output many variations of that person's face with different poses and attributes. This is invaluable for training and testing facial recognition systems without needing to collect vast amounts of real-world photos.
Use this if you need to create a large-scale, controlled dataset of synthetic face images for training or evaluating facial recognition models.
Not ideal if you require entirely realistic, unconstrained face images from diverse real-world scenarios or are not working on facial recognition tasks.
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86
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6
Language
Python
License
MIT
Category
Last pushed
Jan 19, 2026
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