A video GAN trained on semantic top-down traffic videos generates 15–25 m field-of-view scenes whose speed, acceleration, spacing, and time-to-collision statistics resemble real Waymo data, with inference below 20 ms.
In: Proceedings of the 18th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
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Extended Field of View Analysis for VideoGAN-based Trajectory Generation
A video GAN trained on semantic top-down traffic videos generates 15–25 m field-of-view scenes whose speed, acceleration, spacing, and time-to-collision statistics resemble real Waymo data, with inference below 20 ms.