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Blog
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.
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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
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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.
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Beating the State of the Art in Object Tracking with Synthetic Data
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How Toyota Research Trains Better Computer Vision Models
Discussion with Toyota Research Institute’s Head of Machine Learning Research Adrien Gaidon
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What is a Parallel Domain?
A Parallel Domain is a virtual world in which we generate synthetic data for training and testing.
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Announcing Our Series A to Accelerate Computer Vision Development
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