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010   $a3-031-87588-5
024 7 $a10.1007/978-3-031-87588-5
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035   $a(Au-PeEL)EBL32163403
035   $a(CKB)39395917900041
035   $a(DE-He213)978-3-031-87588-5
035   $a(EXLCZ)9939395917900041
100   $a20250619d2025      u|         0
101 0 $aeng
135   $aurcnu||||||||
181   $ctxt$2rdacontent
182   $cc$2rdamedia
183   $acr$2rdacarrier
200 10$aIntelligent and Efficient Video Moment Localization /$fby Meng Liu, Yupeng Hu, Weili Guan, Liqiang Nie
205   $a1st ed. 2025.
210  1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025.
215   $a1 online resource (229 pages)
311 08$a3-031-87587-7 
327   $aChapter 1: Introduction -- Chapter 2: Semantic Enhanced Video Moment Localization -- Chapter 3: Semantic Alignment Video Moment Localization -- Chapter 4: Semantic Pruning Video Moment Localization -- Chapter 5: Semantic Collaborative Video Moment Localization -- Chapter 6: Weakly-Supervised Video Moment Localization -- Chapter 7: Efficient Hashing based Video Moment Localization -- Chapter 8: Research Frontiers.
330   $aThis book provides a comprehensive exploration of video moment localization, a rapidly emerging research field focused on enabling precise retrieval of specific moments within untrimmed, unsegmented videos. With the rapid growth of digital content and the rise of video-sharing platforms, users face significant challenges when searching for particular content across vast video archives. This book addresses how video moment localization uses natural language queries to bridge the gap between video content and semantic understanding, offering an intuitive solution for locating specific moments across diverse domains like surveillance, education, and entertainment. This book explores the latest advancements in video moment localization, addressing key issues such as accuracy, efficiency, and scalability. It presents innovative techniques for contextual understanding and cross-modal semantic alignment, including attention mechanisms and dynamic query decomposition. Additionally, the book discusses solutions for enhancing computational efficiency and scalability, such as semantic pruning and efficient hashing, while introducing frameworks for better integration between visual and textual data. It also examines weakly-supervised learning approaches to reduce annotation costs without sacrificing performance. Finally, the book covers real-world applications and offers insights into future research directions.
606   $aImage processing$xDigital techniques
606   $aComputer vision
606   $aArtificial intelligence$xData processing
606   $aQuantitative research
606   $aMultimedia systems
606   $aComputer Imaging, Vision, Pattern Recognition and Graphics
606   $aData Science
606   $aData Analysis and Big Data
606   $aMultimedia Information Systems
615  0$aImage processing$xDigital techniques.
615  0$aComputer vision.
615  0$aArtificial intelligence$xData processing.
615  0$aQuantitative research.
615  0$aMultimedia systems.
615 14$aComputer Imaging, Vision, Pattern Recognition and Graphics.
615 24$aData Science.
615 24$aData Analysis and Big Data.
615 24$aMultimedia Information Systems.
676   $a006
700   $aLiu$b Meng$01830182
701   $aHu$b Yupeng$01830183
701   $aGuan$b Weili$01799327
701   $aNie$b Liqiang$01783719
801  0$bMiAaPQ
801  1$bMiAaPQ
801  2$bMiAaPQ
906   $aBOOK
912   $a9911011778903321
996   $aIntelligent and Efficient Video Moment Localization$94400464
997   $aUNINA