The game and film industries have provided us with a wealth of dynamic 3D content, letting you quickly bootstrap our synthetic data projects and start iterating on the data. With the Unity Perception package, you can import those assets, set them up for randomization, and generate highly varied datasets very quickly.

The Unity AI organization is working on amazing research and products in the areas of robotics, computer vision, and machine learning. Our AI summer interns all worked on relevant, AI-related projects that actually impact our products.

Designing computer vision solutions for home interior applications is complex, as gathering diverse and accurate data can be expensive, time consuming, and riddled with privacy concerns. Read on to find out how Unity’s synthetic dataset generation tools and services enable the development of more capable computer vision applications for the home while mitigating roadblocks and challenges.

Learn how to leverage High Definition Render Pipeline (HDRP) settings to maximize performance and achieve powerful graphics all at once.

Our Made with Unity: AI series showcases Unity projects made by creators for a range of purposes that involve our artificial intelligence products. In this example, we feature a recent submission to the OpenCV Spatial AI competition that showcases robotics, computer vision, reinforcement learning, and augmented reality in Unity in an impressive suite of examples.

The ML-Agents Toolkit allows researchers and game developers to build and train agents in Unity environments using Reinforcement Learning (RL). RL is useful when it is easier to specify what task an agent needs to complete rather than how to do it. An agent learns to select actions to complete a task on its own using observations from its environment and a task reward signal. Here’s how our interns improved our RL and ML-agents this summer.