Web: http://arxiv.org/abs/2110.13939

June 17, 2022, 1:13 a.m. | Wenhao Ding, Haohong Lin, Bo Li, Ding Zhao

cs.CV updates on arXiv.org arxiv.org

Generating safety-critical scenarios, which are crucial yet difficult to
collect, provides an effective way to evaluate the robustness of autonomous
driving systems. However, the diversity of scenarios and efficiency of
generation methods are heavily restricted by the rareness and structure of
safety-critical scenarios. Therefore, existing generative models that only
estimate distributions from observational data are not satisfying to solve this
problem. In this paper, we integrate causality as a prior into the scenario
generation and propose a flow-based generative framework, …

arxiv cv flow generation safety safety-critical

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