
Teil der Reihe: Computer Science (R0)
Large Vision-Language Models
Inhaltsangabe
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.
Produktdetails
- Erscheinungsdatum: 30.08.2025
- Autor/Autorin: Kaiyang Zhou
- Reihe: Computer Science (R0)
- Format: E-Book
- Dateiformat: PDF
- Kopierschutz: Wasserzeichen
- Dateigröße: 69.9 MB
- Verlag: SPRINGER
- Sprache: Englisch
- Umfang: 429 Seiten
- ISBN: 9783031949692
- Lieferung: Sofort per Download
- Hinweis: Sofort per Download lieferbar. Kein physischer Versand.
- Kompatibilität: Lesbar auf Geräten und Apps mit PDF-Unterstützung.
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