Abstract: A method may include training a machine learning model to perform a first task before training the machine learning model to perform the second task. The machine learning model includes a generator network and a discriminator network. The training includes training, based on a first training sample associated with the first task, the discriminator network to perform the first task. The generator network may be trained to generate a first synthetic training sample emulating the first training sample. The discriminator network trained to perform the first task may be reinitialized in order for the discriminator network to be trained, based on a second training sample, to perform the second task. The reinitialized discriminator network may be further retrained, based on the first synthetic training sample, to perform the first task. Related systems and articles of manufacture, including computer program products, are also provided.

Abstract: A method for generating synthetic data is provided. The method includes retrieving, from a database, a set of authentic base class images. The method further includes generating a three dimensional mesh of a base class. The method further includes retrieving, from the database, a set of textual descriptions. The method further includes retrieving a set of authentic novel class images. The method further includes generating, at a first neural network, a set of synthetic novel class images, the generating based on at least the three dimensional mesh, the set of textual descriptions, and/or the set of authentic novel class images. The method further includes training, based on at least the set of synthetic novel class images, a second neural network, the second neural network ranking the set of synthetic novel class images and outputting a set of highest ranked synthetic images from the set of synthetic novel class images.

Abstract: A method may include training a machine learning model to perform a first task before training the machine learning model to perform the second task. The machine learning model includes a generator network and a discriminator network. The training includes training, based on a first training sample associated with the first task, the discriminator network to perform the first task. The generator network may be trained to generate a first synthetic training sample emulating the first training sample. The discriminator network trained to perform the first task may be reinitialized in order for the discriminator network to be trained, based on a second training sample, to perform the second task. The reinitialized discriminator network may be further retrained, based on the first synthetic training sample, to perform the first task. Related systems and articles of manufacture, including computer program products, are also provided.