Abstract
In this technical report, we present the top-performing LiDAR-only solutions for 3D detection, 3D tracking and domain adaptation three tracks in Waymo Open Dataset Challenges 2020. Our solutions for the competition are built upon our recent proposed PV-RCNN 3D object detection framework. Several variants of our PV-RCNN are explored, including temporal information incorporation, dynamic voxelization, adaptive training sample selection, classification with RoI features, etc. A simple model ensemble strategy with non-maximum-suppression and box voting is adopted to generate the final results. By using only LiDAR point cloud data, our models finally achieve the 1st place among all LiDAR-only methods, and the 2nd place among all multi-modal methods, on the 3D Detection, 3D Tracking and Domain Adaptation three tracks of Waymo Open Dataset Challenges. Our solutions will be available at this https URL
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URL
https://arxiv.org/abs/2008.12599