This is an absolute must-watch for anyone serious about real-time pose estimation.
Deploying pose estimation models in real-world applications often faces challenges related to computational constraints and real-time performance requirements. Additionally, varying environmental conditions and diverse human appearances can degrade the model’s accuracy and robustness in practical scenarios.
Join Eugene Khvedchenya, a Kaggle Grandmaster and deep learning engineer at Deci, for a live webinar that delves deep into the intricacies of pose estimation and offers unparalleled insights on how to optimize it for better accuracy and real-time performance.
Watch now to:
- Discover common challenges in deployment of pose estimation models: Understand the limitations and ways to overcome them.
- Learn the latest techniques & best practices: Stay updated with the most effective strategies in the industry.
- Interactive Q&A: Learn from pressing questions answered by our experts.
If you want to learn more about optimizing your computer vision applications, book a demo here.
