Systems and methods for vision-language distribution alignment

A method for vision-language distribution alignment, the method comprising:

• receiving, via a data interface, a first batch of image samples and a second batch of text samples;
• encoding, by an image encoder, the first batch of image samples into a first plurality of image feature representations stored at a first feature queue;
• encoding, by a text encoder, the second batch of text samples into a second plurality of text feature representations stored at a second feature queue;
• computing an image-to-image similarity between at least one image feature representation and the first plurality of image feature representations in the first feature queue;
• computing a text-to-text similarity between at least one text feature representation all and the second plurality of text feature representations in the second feature queue;
• computing a cross-modal alignment loss based on the image-to-image similarity and the text-to-text similarity;
• and
• updating the image encoder and the text encoder based at least in part on the cross-modal alignment loss.

A non-transitory processor-readable storage medium storing a plurality of processor-executable instructions for vision-language distribution alignment, the instructions being executed by a processor to perform operations comprising:

• receiving, via a data interface, a first batch of image samples and a second batch of text samples;
• encoding, by an image encoder, the first batch of image samples into a first plurality of image feature representations stored at a first feature queue;
• encoding, by a text encoder, the second batch of text samples into a second plurality of text feature representations stored at a second feature queue;
• computing an image-to-image similarity between at least one image feature representation and the first plurality of image feature representations in the first feature queue;
• computing a text-to-text similarity between at least one text feature representation and the second plurality of text feature representations in the second feature queue;
• computing a cross-modal alignment loss based on the image-to-image similarity and the text-to-text similarity;
• and
• updating the image encoder and the text encoder based at least in part on the cross- modal alignment loss.