开源仓库
基于激光雷达的人体动作数据集(humanlidarmotion)

本数据集CMD与域自适应方法DIG的提出,将为跨体制域自适应三维目标检测研究提供数据支撑和方法参考,推进三维目标检测算法在不同三维传感器间迁移能力的相关研究。CMD覆盖了城区、郊区、乡村、公路、桥梁、隧道、校园等场景,由从明亮到昏暗五种光照强度等级的50个序列组成,每个传感器包含10000帧数据。
激光雷达人体动作捕捉数据集

HiSC4D通过融合IMU、LiDAR和SLAM的多模态数据,构建了一个多阶段的联合优化框架,有效解决了IMU漂移问题,并显著提升了场景重建精度,扩展了空间、人体动作和互动捕捉的范围。
Road Scene Labeled Dataset

This datase provides point cloud data together with multi-view images on object level.
Outdoor road marking dataset

The is a road marking dataset for outdoor scenes. 12 segments of road point clouds are provided in this dataset, each segment is about 300 meters long. Each segment of the point cloud provides semantic and instance labeling of road marking. The acquisition equipment is RIEGL VMX-450, and the acquisition location is Xiamen, Fujian Province.
Indoor Laser Scanning Dataset

Indoor laser scanning dataset provides fours indoor point clouds data based on SLAM-mapping process. The scenes include large scale indoor parking lots, corridor and multiple rooms. This dataset also includes line framework extraction results of the scenes and provides a brief description of the indoor scene.
Colored Indoor Laser Scanning Dataset

Colored indoor laser scanning dataset provides point clouds data with RGB information based on multisensor calibration and LiDAR SLAM mapping methods.
Frame-level labeled Dataset

A manually labeled frame-by-frame indoor dataset with more than 12,000 frames and nine semantic categories.
Indoor LiDAR-based SLAM dataset

The indoor LiDAR-based SLAM dataset consists of three scenes captured by multi-beam laser scanners in indoor environments with various complexity. The original scan frame data from scanners are provided. Users can test their LiDAR SLAM algorithm on these data.
BIM Feature Extraction Dataset

The BIM feature extraction dataset contains data from three indoor scenes with various complexity. For each of the scenes, raw data (point cloud in LAS format) and corresponding BIM line framework (in OBJ format) are provided. Users can evaluate their methods using the downloaded reference line frameworks. Evaluation by submitting will open for further performance comparison. The evaluation results will be listed on the webpage.
Indoor Positioning Dataset

The indoor positioning dataset consists of five data sequences acquired in indoor environments with various complexity. Data sequences of sensor records from smartphones are provided. Users can test their positioning algorithm on these data.