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A modular approach: 3D content production, project-specific simulation preparation, controllable visual-data generation and model evaluation.

Simulation readiness depends on the target stack. Scale, coordinate systems, pivots, collision meshes, articulation, material properties, metadata, performance and simulator compatibility must be reviewed for each project. A visual render does not demonstrate physics validation.

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• Robot perception: visual data for detection, classification, segmentation and localization.
• Scenario development: controlled variations in object arrangements, camera viewpoints, lighting, occlusion and clutter.
• Industrial inspection: training and evaluation data for visual quality and component-recognition workflows.

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Real synthetic visual sample

SeaDrone synthetic maritime image supplied by Vivid. Shown as an RGB rendering sample. It is not a demonstration of collision geometry, physics properties, robot articulation or simulator-ready export.

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Synthetic datasets & Computer Vision

Once scene and asset requirements have been defined, Vivid can support visual dataset generation, scenario design and computer-vision workflows, including labels and exports specified for the use case. Confirm modalities, annotation types and formats in the project scope.

Explore public datasets

These example datasets are hosted under the Vivid3Dai organization.

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Interactive Vivid Lab

A separate public Lab can showcase asset-readiness criteria, visual-data samples and dataset previews. This Organization Card does not run a simulator.

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