| 书目名称 | Dense Image Correspondences for Computer Vision | | 编辑 | Tal Hassner,Ce Liu | | 视频video | | | 概述 | Provides in-depth coverage of dense-correspondence estimation.Covers both the breadth and depth of new achievements in dense correspondence estimation and their applications.Includes information for d | | 图书封面 |  | | 描述 | This book describes the fundamental building-block of many new computer vision systems: dense and robust correspondence estimation. Dense correspondence estimation techniques are now successfully being used to solve a wide range of computer vision problems, very different from the traditional applications such techniques were originally developed to solve. This book introduces the techniques used for establishing correspondences between challenging image pairs, the novel features used to make these techniques robust, and the many problems dense correspondences are now being used to solve. The book provides information to anyone attempting to utilize dense correspondences in order to solve new or existing computer vision problems. The editors describe how to solve many computer vision problems by using dense correspondence estimation. Finally, it surveys resources, code and data, necessary for expediting the development of effective correspondence-based computer vision systems. | | 出版日期 | Book 2016 | | 关键词 | Annotation Propagation; Data Driven; Dense Correspondence Estimation; Dense Correspondences; Dense Pixel | | 版次 | 1 | | doi | https://doi.org/10.1007/978-3-319-23048-1 | | isbn_softcover | 978-3-319-35914-4 | | isbn_ebook | 978-3-319-23048-1 | | copyright | Springer International Publishing Switzerland 2016 |
The information of publication is updating
|
|
发表于 2025-3-21 18:19:12
