Video Object Segmentation: Tasks, Datasets, and Methods

Xu, Ning/ Lin, Weiyao/ Lu, Xiankai/ Wei, Yunchao

ISBN 10: 3031446550 ISBN 13: 9783031446559
Edité par Springer-Nature New York Inc, 2024
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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.

À propos de l?auteur: Ning Xu, Ph.D., is a Research Scientist at Adobe Research. He received his Ph.D. in Electrical and Computer Engineering from the University of Illinois at Urbana-Champaign. He was an organizer of the first and second LSVOS Challenge in ECCV 2018 and ICCV 2019. He is also an organizer for the ACM MM 2020 grand challenge "Large-scale Human-centric Video Analysis in Complex Events" and ACCV 2020 tutorial "Spatial -Temporal Parsing of Objects: From Segmentation to Actions". His research interests include image and video segmentation.
Weiyao Lin, Ph.D. is a Professor at Shanghai Jiao Tong University. He received his B.S. and M.E. from Shanghai Jiao Tong University and Ph.D. degree from the University of Washington, all in electrical engineering.
Xiankai Lu, Ph.D., is a Research Professor at Shandong University. Prior to this role, he was a research associate with Inception Institute of Artificial Intelligence at Abu Dhabi, UAE. Dr. Lu received a B. E. from the Department of Automation at Shan Dong University.
Yunchao Wei, Ph.D, is a Professor in the Center of Digital Media Information Processing at Beijing Jiaotong University. He received his Ph.D. from Beijing Jiaotong University. His current research interests include visual recognition with imperfect data, image/video segmentation and object detection, and multi-modal perception.

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Titre : Video Object Segmentation: Tasks, Datasets, ...
Éditeur : Springer-Nature New York Inc
Date d'édition : 2024
Reliure : Hardcover
Etat : Brand New

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Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides a thorough introduction to the most common problem settings, including semi-supervised VOS and unsupervised VOSDiscusses recent progress in video object segmentation, including new datasets, methods, and experimental findingsAids r. N° de réf. du vendeur 1071297982

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Buch. Etat : Neu. Video Object Segmentation | Tasks, Datasets, and Methods | Ning Xu (u. a.) | Buch | viii | Englisch | 2023 | Springer | EAN 9783031446559 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand. N° de réf. du vendeur 127476513

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Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. N° de réf. du vendeur 9783031446559

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Buch. Etat : Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 196 pp. Englisch. N° de réf. du vendeur 9783031446559

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Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 187 pp. Englisch. N° de réf. du vendeur 9783031446559

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