Large Vision-Language Models, Gebunden
Large Vision-Language Models
- Pre-training, Prompting, and Applications
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- Herausgeber:
- Kaiyang Zhou, Ziwei Liu, Peng Gao
- Verlag:
- Springer, 08/2025
- Einband:
- Gebunden
- Sprache:
- Englisch
- ISBN-13:
- 9783031949685
- Umfang:
- 448 Seiten
- Gewicht:
- 832 g
- Maße:
- 241 x 160 mm
- Stärke:
- 30 mm
- Erscheinungstermin:
- 31.8.2025
- Serie:
- Advances in Computer Vision and Pattern Recognition
- Hinweis
-
Achtung: Artikel ist nicht in deutscher Sprache!
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Klappentext
Part 1: Pre-training and Datasets.- Chapter 1: LAION-5B: A Massive Open Image-Text Dataset.- Chapter 2: Efficient Training of Large-Scale Vision-Language Models.- Chapter 3: Scaling Laws for Contrastive Language-Image Learning.- Chapter 4: Scaling Up Vision-Language Models for Generic Tasks.- Chapter 5: Searching for Next-Gen Multimodal Datasets.- Part 2: Prompting and Generalization.- Chapter 6: Soft Prompt Learning for Vision-Language Models.- Chapter 7: Unified Prompting for Vision and Language.- Chapter 8: Zero-Shot Image Classification with Custom Prompts.- Chapter 9: Enhancing Vision-Language Models with Feature Adapters.- Chapter 10: Automatic Optimization of Prompting Architectures.- Chapter 11: Open-Vocabulary Calibration for VL Models.- Part 3: Applications.- Chapter 12: Open-Vocabulary DETR with Conditional Matching.- Chapter 13: Extracting Dense Labels from CLIP.- Chapter 14: PointCLIP: Understanding Point Clouds with VL.- Chapter 15: Diffusion-Based Relation Inversion from Images.- Chapter 16: Text-to-Video Generation.- Chapter 17: Text-Driven Human Motion Generation.- Chapter 18: Zero-Shot Text-Driven 3D Avatar Generation.- Chapter 19: Zero-Shot Text-Driven HDR Panorama Generation.
