We build mocap systems that learn from synthetic motion at a scale real-world capture can't match, and ship them as fmotion.ai.
fmotion turns ordinary video into joint-accurate motion capture you can drop into Blender, Unreal, Unity or Maya. No suits, no markers, no rigs, just video in, motion out.
Visit fmotion.ai →Real-world mocap datasets are small, expensive, and miss the long tail. We built a synthetic data pipeline that produces motion sequences at a scale and diversity unreachable from physical capture, and the accuracy gains compound across every category we measure.
Reduction in mean per-joint position error against our internal benchmark suite, model-over-model after synthetic-data fine-tuning.
Reduction in inter-frame jitter on dynamic motion sequences. Frame-to-frame acceleration error drops sharply where prior models struggle.
Range of motion categories where the trained model retains under-threshold accuracy, relative to a baseline trained on physical capture only.
[email protected] across our held-out evaluation set after the synthetic-data training pass. Baseline reaches the high 80s.
Any camera, any angle, any frame rate. No depth sensor, no multi-camera rig, no calibration.
Spine, limbs, hands and head, exported as industry-standard skeleton hierarchies, ready for retargeting.
Sports, dance, stunts and combat. The synthetic training set covers motion ranges far beyond what physical actors safely produce.
Inferred joint positions when the camera loses sight, limbs behind props, bodies behind bodies, off-frame extremities.
Industry-standard exports. Drop into Blender, Maya, Unreal, Unity. No translation layer.
Encrypted upload, isolated processing, deleted on export. No training on customer data.
Custom pipelines, research collaborations, or just a question about the model, we'd like to hear from you.