Synthetic Data for Visual Human Behavior Analysis with SKY ENGINE AI
More than 70% of computer vision developers struggle with sourcing training data. Join Jakub Pietrzak, CTO of SKY ENGINE AI, in a free webinar where he will describe how synthetic training data can solve this problem. As an example, he’ll focus on how 3D generative AI combines with physically-based rendering to train deep learning models for the analysis of human faces, bodies and behavior. He will also demonstrate example datasets created in the SKY ENGINE AI Synthetic Data Cloud, along with inference results from models trained purely on synthetic data.
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Human-related applications of computer vision and AI are growing rapidly in both number and diversity. From medicine to retail to manufacturing and security, AI-powered solutions will soon be ubiquitous in our lives. In the midst of this flux, one constant remains: the need for high-quality deep learning model training data. Face and body analysis-related use cases such as face recognition and segmentation, gaze estimation and facial expression analysis make this requirement even more critical.
Training with manually-labeled real-world images has historically been the most common approach. However, this approach has multiple drawbacks, including:
- Legal and ethical concerns
- Labeling accuracy issues
- Low-diversity datasets
- Context bias
- A lack of 3D information in ground truth
These obstacles are often difficult or impossible to eliminate. SKY ENGINE AI's approach leverages synthetic data to train computer vision models, providing an alternative methodology that bypasses these issues, and that offers support for different modalities including visible light, near infrared, radar and lidar.
In this webinar, Jakub Pietrzak, Chief Technology Officer for SKY ENGINE AI, will explain how 3D generative AI combines with physically-based rendering to train deep learning models for the analysis of human faces, bodies and behavior. He will also demonstrate example datasets created in the SKY ENGINE AI Synthetic Data Cloud, along with inference results from models trained purely on synthetic data. A question-and-answer session will follow the presentation.
Jakub Pietrzak leads GPU-accelerated research, data science, and machine learning algorithms development at SKY ENGINE AI. He is a computer vision expert with 20+ years experience in machine learning, ray tracing, and digital image processing. Jakub has worked on deep learning-powered motion-capture systems for the biggest movie studios in Europe and was involved in medical imaging research projects at the Warsaw Center of Oncology.
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Watch the videoHuman-related applications of computer vision and AI are growing rapidly in both number and diversity. From medicine to retail to manufacturing and security, AI-powered solutions will soon be ubiquitous in our lives. In the midst of this flux, one constant remains: the need for high-quality deep learning model training data. Face and body analysis-related use cases such as face recognition and segmentation, gaze estimation and facial expression analysis make this requirement even more critical.
Training with manually-labeled real-world images has historically been the most common approach. However, this approach has multiple drawbacks, including:
- Legal and ethical concerns
- Labeling accuracy issues
- Low-diversity datasets
- Context bias
- A lack of 3D information in ground truth
These obstacles are often difficult or impossible to eliminate. SKY ENGINE AI's approach leverages synthetic data to train computer vision models, providing an alternative methodology that bypasses these issues, and that offers support for different modalities including visible light, near infrared, radar and lidar.
In this webinar, Jakub Pietrzak, Chief Technology Officer for SKY ENGINE AI, will explain how 3D generative AI combines with physically-based rendering to train deep learning models for the analysis of human faces, bodies and behavior. He will also demonstrate example datasets created in the SKY ENGINE AI Synthetic Data Cloud, along with inference results from models trained purely on synthetic data. A question-and-answer session will follow the presentation.
Jakub Pietrzak leads GPU-accelerated research, data science, and machine learning algorithms development at SKY ENGINE AI. He is a computer vision expert with 20+ years experience in machine learning, ray tracing, and digital image processing. Jakub has worked on deep learning-powered motion-capture systems for the biggest movie studios in Europe and was involved in medical imaging research projects at the Warsaw Center of Oncology.