Titlebook: Computational Methods for Integrating Vision and Language; Kobus Barnard Book 2016 Springer Nature Switzerland AG 2016

奖牌

Laura Rojas Vidaurreta,Jonatas Maia da Costa, perhaps the scene has people and cars) carries meaning. By contrast, a single pixel or region does not tell us much about what was in front of the camera when the picture was taken. In short, for many tasks, our representations need to support localization and context.

开始从未

左右连贯

The Importance of Hegelian Recognition,dering; (2) producing sequential output (e.g., image and video captioning); and (3) interpreting more complex queries for image search and visual question and answering. Some of these efforts are covered in this chapter.

不容置疑

Extracting and Representing Visual Information,, perhaps the scene has people and cars) carries meaning. By contrast, a single pixel or region does not tell us much about what was in front of the camera when the picture was taken. In short, for many tasks, our representations need to support localization and context.

Accommodation

alcohol-abuse

Sequential Structure,dering; (2) producing sequential output (e.g., image and video captioning); and (3) interpreting more complex queries for image search and visual question and answering. Some of these efforts are covered in this chapter.

GREEN

fabricate

Subjectivity in the American Protest Novelta, training systems to extract semantic content from either visual and linguistic data, and develop machine representations that are indicative of higher level semantics and thus can support intelligent machine behavior.

删减

Introduction,ta, training systems to extract semantic content from either visual and linguistic data, and develop machine representations that are indicative of higher level semantics and thus can support intelligent machine behavior.

多节

2153-1056 l applications. Examples of dual visual-linguistic data includes images with keywords, video with narrative, and figures in documents. We consider two key task-driven themes: translating from one modality to another (e.g., inferring annotations for images) and understanding the data using all modali