Large Vision-Language Models
Pre-training, Prompting, and Applications
Springer
ISBN 978-3-031-94968-5
Standardpreis
Bibliografische Daten
Fachbuch
Buch. Hardcover
2025
In englischer Sprache
Umfang: xvii, 429 S.
Format (B x L): 15,5 x 23,5 cm
Verlag: Springer
ISBN: 978-3-031-94968-5
Weiterführende bibliografische Daten
Das Werk ist Teil der Reihe: Advances in Computer Vision and Pattern Recognition
Produktbeschreibung
Large Vision-Language Models begins by exploring the fundamentals of large vision-language models, covering architectural designs, training techniques, and dataset construction methods. It then examines prompting strategies and other adaptation methods, demonstrating how these models can be effectively fine-tuned to address a wide range of downstream tasks. The final section focuses on the application of vision-language models across various domains, including open-vocabulary object detection, 3D point cloud processing, and text-driven visual content generation and manipulation.
Beyond the technical foundations, the book explores the wide-ranging applications of vision-language models (VLMs), from enhancing image recognition systems to enabling sophisticated visual content generation and facilitating more natural human-machine interactions. It also addresses key challenges in the field, such as feature alignment, scalability, data requirements, and evaluation metrics. By providing a comprehensive roadmap for both newcomers and experts, this book serves as a valuable resource for understanding the current landscape, limitations, and future directions of VLMs, ultimately contributing to the advancement of artificial intelligence.
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