Move to better face recognition models

Describe the feature you'd like to request

I have installed Recognize together with Memories and so far everything works: Recognize scans my images for faces and groups them together. Great!

Yesterday, just for testing, i set up an instance of immich and loaded the same photo library i have stored in my Nextcloud. Immich currently uses the buffalo_l model from InsightFace for facial recognition, and after scanning i was blown away by the accuracy: The model not only found way more pictures, it was also way better at assigning them to the right person. To give you some numbers: recognize found 706 pictures of me, immich with buffalo_l found 3780 pictures. All correctly assigned with sometimes mind-blowing accuracy.

Since the results were that good, i thought about suggesting replacing of the face recognition model, e.g. with buffalo_l or similar, to further promote Nextcloud as the main storage for photos. I am aware that this is not a one-click replacement and might require a lot of effort or additional work, but as this might also affect ongoing discussions, e.g. https://github.com/nextcloud/recognize/discussions/865 regarding undetected faces, i wanted to share my thoughts with you.

Describe the solution you'd like

Move to an improved face recognition model

Describe alternatives you've considered

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The issue names no files or tests; start by reviewing the current face-recognition implementation and the linked discussion about undetected faces. Compare the existing model with InsightFace's buffalo_l, then define the integration approach and accuracy criteria before implementation.