DeViSE: A Deep Visual-Semantic Embedding Model

This paper presents a new deep visual-semantic embedding model trained to identify visual objects using both labeled image data as well as semantic information gleaned from unannotated text and shows that the semantic information can be exploited to make predictions about tens of thousands of image labels not observed during training.