Benchmark Datasets

City-Facade is a large-scale urban building facade dataset for semantic-level and instance-level segmentation from MLS LiDAR point clouds. It consists of labeled point clouds (with 9 classes for building facades) as well as unlabeled data (point clouds of street landscapes). The data collection area encompasses a variety of streets in Xiamen, China, with distinct architectural styles. We believe that our City-Facade will faciliate feature research on point cloud semantic or instance segmentation, urban understanding and modeling, point cloud completion, etc. Welcome to download and make use of City-Facade.
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DBNet is a comprehensive large-scale dataset that includes 3D point cloud data, video images, GNSS data, and driver behavior metrics such as speed and direction. It Covers over 1,000 kilometres in Xiamen with different types of roads. DBNet provides city-level 3D point cloud with coresponding 2D video images, serving as a robust foundation for decision-making in autonomous driving. It has been widely used by more than 600 organizations and individuals across the world, including MIT, Google, etc. Welcome to download and make use of DBNet.
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