Shypd.aiThe largest open index of AI toolspseudo_lidar is an open-source research tool that bridges the gap in 3D object detection for autonomous driving. It converts image-based depth maps to pseudo-LiDAR representations, enabling the use of existing LiDAR-based detection algorithms.
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pseudo_lidar is an open-source project from CVPR 2019 focused on advancing 3D object detection for autonomous driving. It addresses the limitations of image-based depth estimation by proposing a novel approach: converting visual depth maps into pseudo-LiDAR representations. This allows researchers to leverage existing, highly accurate LiDAR-based detection algorithms with more affordable camera data. The project provides guidance and code for training stereo depth estimators and 3D object detectors using the KITTI object detection benchmark, along with pre-trained models and pseudo-LiDAR point clouds. It supports integration with popular object detection models like AVOD and Frustum-PointNets, offering a significant improvement in detection accuracy for image-based systems.
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