Our per-camera networks analyze raw images to perform semantic segmentation, object detection and monocular depth estimation. Our birds-eye-view networks take video from all cameras to output the road layout, static infrastructure and 3D objects directly in the top-down view. Our networks learn from the most complicated and diverse scenarios in the world, iteratively sourced from our fleet of nearly 1M vehicles in real time. A full build of Autopilot neural networks involves 48 networks that take 70, 000 GPU hours to train 🔥. Together, they output 1,000 distinct tensors (predictions) at each timestep. https://www.tesla.com/autopilotAI https://www.tesla.com/sites/default/files/images/careers/autopilot/network. mp4
【 以下文字转载自 Automobile 讨论区 】
发信人: Caravel (克拉维尔), 信区: Automobile
标 题: Tesla的autopilot感知系统内部表象
发信站: BBS 未名空间站 (Fri Jan 31 13:36:24 2020, 美东)
感知非常精准啊
Our per-camera networks analyze raw images to perform semantic segmentation, object detection and monocular depth estimation. Our birds-eye-view
networks take video from all cameras to output the road layout, static
infrastructure and 3D objects directly in the top-down view. Our networks
learn from the most complicated and diverse scenarios in the world,
iteratively sourced from our fleet of nearly 1M vehicles in real time. A
full build of Autopilot neural networks involves 48 networks that take 70,
000 GPU hours to train 🔥. Together, they output 1,000 distinct
tensors (predictions) at each timestep.
https://www.tesla.com/autopilotAI
https://www.tesla.com/sites/default/files/images/careers/autopilot/network.
mp4