公开数据集统一放在 root/datasets 路径下,大家可以通过复制/软链接进行调用哦!

数据集详情页涵盖所属标签以及数据集的基本说明。数据集格式等具体信息可点击数据集来源链接查看哦~

SemanticKITTI

数据集大小80.0 GB

更新时间2021-08-02 16:36:54

数据集标签
计算机视觉语义分割基准数据集点云语义分割

数据集路径

数据集无需解压和下载,可直接在代码中更改数据集路径使用

/datasets/semantic-kitti/

数据集简介

SemanticKITTI is a large-scale outdoor-scene dataset for point cloud semantic segmentation derived from the KITTI Vision Odometry Benchmark. The total point clouds 23201 for training 20351 for testing

数据集说明

We present a large-scale dataset based on the KITTI Vision Benchmark and we used all sequences provided by the odometry task. We provide dense annotations for each individual scan of sequences 00-10, which enables the usage of multiple sequential scans for semantic scene interpretation, like semantic segmentation and semantic scene completion. The remaining sequences, i.e., sequences 11-21, are used as a test set showing a large variety of challenging traffic situations and environment types. Labels for the test set are not provided and we use an evaluation service that scores submissions and provides test set results. Classes The dataset contains 28 classes including classes distinguishing non-moving and moving objects. Overall, our classes cover traffic participants, but also functional classes for ground, like parking areas, sidewalks.