In particular, we aim to determine which language model yields knowledge that is most suitable for use in Computer Vision.
we test a variety of language models and a linguistically mined knowledge base within two computer vision scenarios: Human action recognition : Recognizing <subject, verb, object> triples based on objects (e.g., car, horse) and scenes (the place that the actions occur, e.g., countryside, forest, office) recognized in images.