World-Model Simulation Data
Simulation-native visual data for world models, made where real footage falls short. Built inside controllable engine environments, a synchronized multi-camera pipeline produces multi-view frames with exact spatial parameters and complete, native annotation — the 3D supervision that internet video simply doesn't carry. Distribution is designed rather than discovered, and built to spec at scale.
Coverage
- Multi-view capture
- Camera pose & intrinsics
- Depth & geometry
- Scene diversity
- Dynamic interaction
- Controllable simulation
Deliverables
- Multi-view video frames
- Camera intrinsics & extrinsics
- Pose & motion parameters
- Depth / segmentation labels
- Structured scene metadata
- Quality tiers & sampling records
From source to acceptance
We don't hand-label a pile and ship it. Every category moves through a closed, instrumented loop — generated to a brief, checked by machines, adjudicated by experts, and traceable end to end — but the path each data type takes is its own.
- 01
Controllable Scene Setup
Scenes are composed inside a controllable simulation environment where lighting, terrain, dynamics, and camera behavior are set as parameters rather than left to chance, so the data distribution is designed rather than harvested.
- 02
Synchronized Multi-View Capture
Several virtual cameras record the same scene in frame-level lockstep under one shared coordinate system, yielding first- and third-person views whose geometry aligns exactly across cameras.
- 03
Motion Governance
Translation, rotation, and jerk are held within defined thresholds and balanced across slow, medium, and fast tiers, so camera motion stays continuous and never skews to a single regime.
- 04
Native Metadata Export
Every frame carries its camera intrinsics, extrinsics, pose trajectory, and the coordinates and headings of scene entities, so the structural supervision is complete without a second manual pass.
- 05
Diversity & Balance Control
Environment, shot, and interaction axes are balanced by design — across lighting, terrain, shot types, and moving elements — to keep the corpus from drifting into bias at the source.
- 06
Tiered QA & Delivery
An automated pipeline verifies alignment accuracy, motion compliance, and diversity ratios, tiers the output by quality, and delivers at scale in formats that drop straight into a training pipeline.
Every run emits a learning signal that feeds back into the source set — the pipeline tightens itself, batch over batch.
Where it’s used
- Pretraining video and 3D world models for spatial consistency
- Training multi-view and free-viewpoint 3D generation
- Grounding embodied and interactive world models in simulated state
Why it matters for training
Essential
Real footage lacks camera parameters and balanced motion; controllable simulation is where that spatial supervision can be produced accurately and at scale.
Notable features
Need a sample or a custom build?
Tell us your spec and scale — we deliver to order.
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