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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.
| Autorius: | Ning Xu, Yunchao Wei, Xiankai Lu, Weiyao Lin, |
| Serija: | Synthesis Lectures on Computer Vision |
| Leidėjas: | Springer Nature Switzerland |
| Išleidimo metai: | 2023 |
| Knygos puslapių skaičius: | 196 |
| ISBN-10: | 3031446550 |
| ISBN-13: | 9783031446559 |
| Formatas: | 246 x 173 x 17 mm. Knyga kietu viršeliu |
| Kalba: | Anglų |
Parašykite atsiliepimą apie „Video Object Segmentation: Tasks, Datasets, and Methods“
