书目名称 | Video Object Segmentation | 副标题 | Tasks, Datasets, and | 编辑 | Ning Xu,Weiyao Lin,Yunchao Wei | 视频video | | 概述 | Provides a thorough introduction to the most common problem settings, including semi-supervised VOS and unsupervised VOS.Discusses recent progress in video object segmentation, including new datasets, | 丛书名称 | Synthesis Lectures on Computer Vision | 图书封面 |  | 描述 | This book provides a thorough overview of recent progress in video object segmentation, providing researchers and industrial practitioners with thorough information on the most important problems and developed technologies in the area. Video segmentation is a fundamental topic for video understanding in computer vision. Segmenting unique objects in a given video is useful for a variety of applications, including video conference, video editing, surveillance, and autonomous driving. Given the revolution of deep learning in computer vision problems, numerous new tasks, datasets, and methods have been recently proposed in the domain of segmentation. The book includes these recent results and findings in large-scale video object segmentation as well as benchmarks in large-scale human-centric video analysis in complex events. The authors provide readers with a comprehensive understanding of the challenges involved in video object segmentation, as well as the most effective methods for resolving them. | 出版日期 | Book 2024 | 关键词 | Video Segmentation; Video Object Segmentation (VOS); Multi-object Tracking (MOT); Video Instance Segmen | 版次 | 1 | doi | https://doi.org/10.1007/978-3-031-44656-6 | isbn_softcover | 978-3-031-44658-0 | isbn_ebook | 978-3-031-44656-6Series ISSN 2153-1056 Series E-ISSN 2153-1064 | issn_series | 2153-1056 | copyright | The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl |
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