100,000 unique multi-room interior scenes

The Aria Synthetic Environments Dataset has been procedurally generated to produce a diverse set of interior scenes. Each scene has a unique room graph connecting multiple rooms, and unique placement of architectural features, such as windows, doors, and pillars.

Populated with high-quality 3D objects

Each of the 100,000 unique scenes, is filled with objects from a digital library, each with high-quality materials and geometry. Objects are diverse and placed according to a simple set of rules that result in a physically-valid location for each object.

Rendered with precisely simulated sensor characteristics

Each simulated sequence is rendered to reflect the sensor characteristics of Project Aria glasses, including simulated lens and sensor characteristics. Inertial data is also simulated using a noise model that reflects Project Aria’s IMU sensors.

Each described with a CAD-like language for architectual entities

Architectural features, such as doors, windows, and pillars, are described with a CAD-like language, including the feature type, location, and dimensions. This unlocks new exciting ways to tackle research challenges related to reconstruction and detection tasks.

Realistic simulated trajectory within each environment

Before rendering each sequence, device trajectories are simulated within each environment according to a set of rules that mirror how users walk while wearing Project Aria glasses. Trajectories are created automatically and ensure a full traversal of each virtual scene.

Semi-dense map representation for each scene

In addition to per-frame depth and instance maps for each sequence, semi-dense point cloud representations are also made available for each environment. These additional representations open up new ways for researchers to tackle reconstruction and detection tasks.