A Practical Guide to Fine-Tuning and Deploying Vision Models

Learn how to efficiently fine-tune and deploy large vision foundation models for production environments in this conference talk from MLOps World. Discover practical techniques for scaling video AI systems across industries like healthcare, robotics, retail, and security without overwhelming compute resources or compromising real-time performance. Explore state-of-the-art approaches to data sampling and temporal-aware augmentation specifically designed for video datasets, while mastering adapter-based tuning methods that optimize large models for domain-specific tasks. Gain insights into scalable optimization strategies and deployment patterns that make vision foundation models viable for production use cases. Understand best practices for processing long or sparse video content with minimal latency, and implement chunk-based inference systems with temporal fusion modules for robust production deployment.