Definition: In this task, you are given a part of an article. Your task is to generate headline (title) for this text. Preferred headlines are under fifteen words.
Input: A Semantic Compositional Network (SCN) is developed<lb>for image captioning, in which semantic concepts (i.e., tags)<lb>are detected from the image, and the probability of each tag<lb>is used to compose the parameters in a long short-term mem-<lb>ory (LSTM) network. The SCN extends each weight matrix of<lb>the LSTM to an ensemble of tag-dependent weight matrices.<lb>The degree to which each member of the ensemble is used<lb>to generate an image caption is tied to the image-dependent<lb>probability of the corresponding tag. In addition to caption-<lb>ing images, we also extend the SCN to generate captions for<lb>video clips. We qualitatively analyze semantic composition<lb>in SCNs, and quantitatively evaluate the algorithm on three<lb>benchmark datasets: COCO, Flickr30k, and Youtube2Text.<lb>Experimental results show that the proposed method signifi-<lb>cantly outperforms prior state-of-the-art approaches, across<lb>multiple evaluation metrics.

Semantic Compositional Networks for Visual Captioning