PRESENTATION: Power Up Your Visual AI with Synthetic Data
Computer Vision is rapidly changing the retail landscape with respect to both the customer experience and in-store day to day logistics like inventory monitoring, brand logo detection, shopper behavior analysis , autonomous checkout. Traditional methods of training models with real world data is becoming a big bottleneck to faster deployment of these vision models. Learn how machine learning and computer vision engineers are using Unity to get faster, cheaper and more unbiased access to high quality synthetic training data and accelerating model deployment.
Key Takeaways: 1) Computer vision is becoming essential in retail with applications ranging from planogram verification to inventory monitoring to cashier-less checkout. 2) Labeled data is critical to computer vision but the traditional approach of using real-world training data is expensive, time-consuming, and often insufficient for training a production-level system. In contrast, synthetic datasets are less expensive, faster to produce, perfectly labeled, and tailored with the end application in mind. 3) Unity has technology to produce synthetic datasets with structured environments and randomizations that lead to robust model performance. This presentation shows samples from a Unity retail-oriented dataset that you can download.
ROUNDTABLE: Solving Retail Challenges with Computer Vision
Join Unity Computer Vision Experts and peers to discuss the rapidly growing field of computer vision and how it is impacting the retail world and some of the challenges associated with deploying computer vision in Retail. This is a freeform session where you can come to the table with your questions and we will have an engaging and interactive conversation around those topics. You can also use this time to talk with the Unity team about using synthetic data for training computer vision models and dig deeper into customer stories and proof points around synthetic data
James has 14 years of experience building and applying simulation and artificial intelligence technologies. He started his career in the simulation brand at Dassault Systèmes, where he worked on mechanical simulation solutions for automotive and aerospace customers. He spent several years managing the delivery of natural language systems for Alexa at Amazon. He has worked as a product manager in the AI organization at Unity since 2019 focusing on Unity Simulation and Unity’s solutions for computer vision and is excited about the next frontiers in AI.