Blog
Testing for the Future: Advancing Perception Through Simulation
Simulation can become transformative, with the promise of testing unlimited scenarios safely in a virtual world. However, previous approaches have struggled to achieve sufficient realism and scale to be trusted by teams to translate to real-world performance. But what if we could recreate the real world as a series of digital twins that give us the knobs and controls to test all of these permutations? It would almost be like driving one mile to generate a thousand miles of useful tests.
Closing the sim-to-real gap with PD Replica
Models trained on PD Replica environments showed a 31.4% improvement over those trained on procedural data in mean average precision (mAP)
Decoding the Streets: Boosting Road Sign Perception with Synthetic Data
Parallel Domain customers experience impressive double-digit performance gains in sign perception tasks.
Boosting Optical Flow with PD Synthetic Data
Parallel Domain (PD) synthetic data improves performance on optical flow tasks by 18.5% by matching flow magnitudes.
Synthetic Data Best Practices for Perception Applications
Synthetic data best practices we learned from working with many perception teams and our internal research.
Not all Synthetic Datasets are Created Equal
Parallel Domain data improves unsupervised domain adaptation performance by 30% vs. GTA with no changes to model architecture.
Parallel Domain Raises $30 Million Series B to super-train AI
The company reimagining how AI learns, realizing an autonomous future for everyone and everything
Parallel Domain Synthetic Data Improves Cyclist Detection
Parallel Domain synthetic data significantly improves performance on rare classes such as bicycles with no changes to model architecture.
