Automatic dataset generation for training computer vision systems and applications

A system comprising:

• one or more processors to:
• obtain, from one or more network resources, information corresponding to one or more first images depicting one or more first objects;
• determine, using one or more language models and based at least on the information, one or more labels indicative of at least one or more classifications corresponding to the one or more first objects;
• associate, as one or more labeled images, the one or more labels with the one or more first images;
• and
• train, using one or more second images of one or more training datasets generated using the one or more labeled images, one or more vision models to classify one or more second objects depicted in one or more input images.

One or more processors comprising:

• processing circuitry to classify, using one or more vision models, one or more objects depicted in one or more image frames associated with an interactive application, wherein the one or more vision models are trained using one or more training datasets that are generated, at least, by:
• obtaining, from one or more network resources, information corresponding to one or more first images depicting the one or more objects;
• associating, based at least on one or more language models processing the information, one or more labels with the one or more first images, the one or more labels indicative of at least one or more classifications associated with the one or more objects;
• and
• appending, to the one or more training datasets and based at least on the one or more first images and the one or more labels, one or more second images depicting one or more second objects having the one or more classifications.