Upsample point cloud data by up to 8X in real-time
Inference time of 5ms (including pre-processing and post-processing) on NVIDIA GTX 1080. Over 98% accurate within 0.01 meters with ground-truth data. We are able to improve range by 10 - 20 meters, and enhance object detection and classification task accuracy by 2X
We provide a highly stable runtime piece in form of a ROS node, and can train and finetune the model to your hardware and environment. We are compatible with multiple software and hardware stacks and LIDAR sensors
Our model is trained on over 1 MN+ LIDAR sweeps from complex environments collected from 8, 16, 64 and 128 channel LIDAR sensors. We have set benchmarks on depth prediction, estimation on the KITTI Vision benchmarking suites (unpublished)
Prana.ai's technology can be used to improve perception in adverse conditions as well as boost the object detection and classification capabilities from high resolution sensors
Reduce the cost of LIDAR sensors by over 90%
A single sweep from a Velodyne VLP16 sensor upsampled by 4X
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