Abstract:Neural implicit representations are drawing a lot of attention from the robotics community recently, as they are expressive, continuous and compact. However, cityscale incremental implicit dense mapping based on sparse LiDAR input is still an under-explored challenge. To this end, we successfully build the first city-scale incremental neural mapping system with a panoptic representation that consists of both environment-level and instance-level modelling. Given a stream of sparse LiDAR point cloud, it maintain… Show more
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