Computer Vision and Learning Group

A machine-learning research group examining why vision models fail on data unlike their training sets. Its methods include adversarial training and multi-source adaptation, and it released the DomainNet cross-domain benchmark dataset; applications include robot grasping, video understanding, and studies of bias in image-captioning models.