- Multi-Object Panoptic Tracking
We introduce and investigate a new perception task that we call MOPT which unifies the conventionally disjoint tasks of semantic segmentation, instance segmentation, and multi-object tracking into a single coherent scene understanding problem. We present PanopticTrackNet and several new baselines to address this task using either LiDAR scans or images.
- Visual Localization in LiDAR Maps
We present novel CNN-based methods for monocular camera localization in LiDAR-maps that are independent of both the map and camera intrinsics. Our networks achieve state-of-the-art performance on KITTI, Argoverse, and Lyft Level5 while being the first deep learning methods to effectively generalize to unseen environments as well as to different sensors.