Abstract: Systems and methods for image search result filtering can include obtaining a search query, determining a plurality of candidate image search results, processing the search query with a generative model to determine a plurality of search result criteria, and refining the plurality of candidate image search results based on determining whether the candidate results satisfy the plurality of search results criteria. The systems and methods can perform a plurality of determinations based on the output of the generative model.

Abstract: Systems and methods for image search result filtering can include obtaining a search query, determining a plurality of candidate image search results, processing the search query with a generative model to determine a plurality of search result criteria, and refining the plurality of candidate image search results based on determining whether the candidate results satisfy the plurality of search results criteria. The systems and methods can perform a plurality of determinations based on the output of the generative model.

Abstract: A computer-implemented method includes receiving an input from a user relating to a concept, automatically obtaining a first set of images from an unlabeled dataset of images based on the input, and obtaining a first rating via the user for each image from the first set of images. The method further includes training a classifier model relating to the concept based on the first set of images rated by the user, automatically obtaining a second set of images from the unlabeled dataset of images based on the classifier model trained based on the first set of images, and obtaining a second rating via the user for each image from the second set of images. The classifier model relating to the concept is retrained based on the first set of images rated by the user and the second set of images rated by the user to obtain an updated classifier model.