Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving

Pseudo-LiDAR from Visual Depth Estimation: Bridging the Gap in 3D Object Detection for Autonomous Driving:

Cornell researchers have discovered that a simpler method, using two inexpensive cameras on either side of the windshield, can detect objects with nearly LiDAR’s accuracy and at a fraction of the cost. The researchers found that analyzing the captured images from a bird’s-eye view rather than the more traditional frontal view more than tripled their accuracy, making stereo camera a viable and low-cost alternative to LiDAR.

“The common belief is that you couldn’t make self-driving cars without LiDARs,” Weinberger said. “We’ve shown, at least in principle, that it’s possible.”

https://autonomous-driving-news.tumblr.com/post/184500890489

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