How to we add a new face into trained face recognition model(inception/resnet/vgg) without retraining complete model?

Question

Is it possible to add a new face features into trained face recognition model, without retraining it with previous faces?

Currently am using facenet architecture,

Answer 1

Take a look in Siamese Neural Network.

Actually if you use such approach you don't need to retrain the model.

Basically you train a model to generate an embedding (a vector) that maps similar images near and different ones far.

After you have this model trainned, when you add a new face it will be far from the others but near of the samples of the same person.

Answer 2

basically, by the mathematics theory behind the machine learning models, you basically need to do another train iteration with only this new data...

but, in practice, those models, especially the sophisticated ones, rely on multiple iterations for training and a various technics of suffering and nose reductions

a good approach can be train of the model from previous state with a subset of the data that include the new data, for a couple of iterations