Training computer vision models on real images has a hard ceiling. Field collection is slow, manual labelling is expensive, and rare scenarios, like occluded targets, adverse weather, low-light conditions, are nearly impossible to capture at scale. Gaia’s procedural engine generates thousands of photorealistic scenes with pixel-perfect labels in hours. Every image comes with ground-truth annotation built in: no labelling queue, no annotation vendor, no delay.
Generate the images when you need them.
Gain complete control over configurations, including scenes, sensors, lighting, activities, labels, and more.
Eliminate privacy concerns by avoiding the use of real-world data.
Step 1.
Create a project and add your first batch. You can add as many batches as you want to each project.
Step 2.
Select the type of environment you need. Add specific objects of interest from a catalog with 3D assets. Your objects of interest are automatically added to each scene.
Step 3.
Select the activities you are interested in. Set various parameters related to the characters you are adding such as age, gender, physical characteristics, ethnicity, etc.
Step 4.
For each batch, select several lighting scenarios from a catalog including various artificial and natural lighting conditions. You can even simulate pictures taken with a flash if desired.
Step 5.
Set your camera’s intrinsic and extrinsic parameters to match your use case. For example, simulate images from a fixed surveillance camera, a drone, satellite image.
Step 6.
Select the labels you need among instance and semantic segmentation, depth image, 3D normal image, albedo image, Lambertian reflectance model, or skeleton key points. Next, choose the number of scenes and images per scene. Then, generate your fully labeled dataset.
Built by the AI Verse engineering team in Sophia Antipolis, France by specialists in 3D animation and computer vision training since 2020.
AI Verse’s procedural engine GAIA eliminates computer vision data bottleneck.
Define your parameters: object classes, environments, lighting, sensor type, weather, viewpoint, etc., and the platform generates fully annotated images in 4 seconds on 1 GPU, at any scale, with pixel-perfect annotation.
PROCEDURAL SCENE GENERATION
Scene Layout: Stochastic Decomposition Trees
3D Standardized Assets Database
3D SCENE
IMAGE
RENDER
Complex Labelling
Materials Database
Light Sources
Virtual Camera Controls and Properties
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