International Business Machines Corporation
TRAINING MULTIMODAL REPRESENTATION LEARNING MODEL ON UNNANOTATED MULTIMODAL DATA

Abstract:

An example system includes a processor to receive unannotated multimodal data. The processor can estimate a probability an associated pair of different modalities in the unannotated multimodal data to be correctly associated using a multimodal similarity function and a local density estimation. The processor can also train a multimodal representation learning model on the unannotated multimodal data using the estimated probability as a weight for the associated pair in a loss function.