Validation of Simulation-Based Testing: Bypassing Domain Shift with Label-to-Image Synthesis

2021 IEEE Intelligent Vehicles Symposium Workshops (IV Workshops)(2021)

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摘要
Many machine learning applications can benefit from simulated data for systematic validation - in particular if real-life data is difficult to obtain or annotate. However, since simulations are prone to domain shift w.r.t. real-life data, it is crucial to verify the transferability of the obtained results.We propose a novel framework consisting of a generative label-to-image synthesis model togeth...
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关键词
Correlation,Systematics,Intelligent vehicles,Conferences,Semantics,Machine learning,Data models
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