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Consider a scenario where I have a model trained on gesture videos (say a 3D ResNet). I am looking for a technique (or a combination) that allows me to further train the model every time I have a new unlabelled datapoint while not resorting to the entire original dataset the model was trained on. In other words I want to utilize the incrementally collected unlabelled data as fast and efficiently as possible.

To my understanding I need a combination of incremental and semi-supervised or unsupervised learning. The latter one to label the unlabelled data and the former to train the model to the new classes.

Any insight is welcome. Thank you.

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