Face models detect faces in photos and video, compare them and check that a live person is in front of the camera. They are used for access control and attendance tracking. Beyond license and accuracy, consider the legal requirements for processing biometric data in your jurisdiction.
The most widely used open toolkit for face detection and recognition. Many identity-preserving image generators are built on it. The pretrained weights are non-commercial.
Transformer-based face recognition from ByteDance, one of the most accurate open models on benchmarks. Weights are published in ONNX format but are non-commercial.
FLUX-based image generation that preserves a face: follows the prompt better and less often pastes the face like a sticker. Research-only license.
Preserves a person's face when generating images from one photo, with less damage to style and background. Versions exist for SDXL and FLUX; the latter runs on a 16 GB card.
One of the first adapters that transfer a face from a photo into a generated image. The SD 1.5 versions run on low-end cards, but the weights are non-commercial.
Generates images with a specific person's face from a single photo, without fine-tuning. Popular in ComfyUI, but the weights are for research only.
Practically the only fully open weight set for single-frame face liveness: it tells a live person from a photo, a screen or a mask. It errs in both directions - a person must be able to appeal a rejection.
An open model can run on your own server: data stays in-house, there is no per-request fee, and the model can be fine-tuned on your documents.
