Making machine perception real
The ANYVERSE synthetic data solution offers the speed, scalability, and visual fidelity needed by machine-learning teams to rapidly progress to high-confidence perception models. ANYVERSE simulates the visual appearance of the real-world with higher accuracy and variability than is practical with other approaches.
Game engines do not accurately mirror reality. ANYVERSE’s physics-based spectral unbiased renderer provides accurate visual quality and ground-truth representation of lighting and the environment.
Speeding up AI training-testing cycles is critical. With ANYVERSE faster perception training-testing iterations are possible, guaranteeing a competitive advantage over teams relying exclusively on real-world datasets.
Fine-grained control of simulation features and variations is key to producing rich datasets in an agile way, increasing confidence and robustness in the perception system.
The best part – there is no need to master complex software. Clients can team up with our engineers to produce custom datasets or get access to a highly scalable SaaS platform to produce the datasets they need.
Rich 3D Scenarios
Predefined and procedurally-generated 3D scenes for urban and suburban areas.
Large library of 3D assets: vehicles, pedestrians, buildings, traffic lights, signs, vegetation, etc.
Agent-based models for traffic and pedestrians.
Unbiased spectral render engine for accurate optical and light simulation.
Physically accurate camera model and support for multiple cameras.
Physically accurate atmospheric and weather models.
LiDAR model based on real-world devices.
Ground Truth Data
Automatic generation of annotated data and pixel-accurate segmentation for every element.
2D/3D bounding boxes.
Multiple data channels: RAW XYZ32 (sensor buffer), RGB32, color screen, object ID, material ID, depth, normal, 3D positions, etc.