graviti logo产品公开数据集关于我们
Demo演示登录
571
0
13
Daimler Mono Pedestrian Detection Benchmark
概要
讨论
代码
活动
33c5e012-8ce2-11eb-b816-506b4b419b4c
517ef2a·
Jun 28, 2021 12:26 AM
·1Commits

Overview

The benchmark involves a large training and test set. The training set contains 15.560 pedestrian samples (image cut-outs at 48x96 resolution) and 6744 additional full images not containing pedestrians for extracting negative samples. The test set contains an independent sequence with more than 21.790 images with 56.492 pedestrian labels (fully visible or partially occluded), captured from a vehicle during a 27 min drive through urban traffic, at VGA resolution (640x480, uncompressed). As such, the dataset is realistic and about one order of magnitude larger than other datasets at time of publication (8.5 Gb). It specifies two evaluation settings: one “generic” (2D bounding box overlap criterion) and one specific to pedestrian detection onboard a vehicle (3D localization criterion, known ground plane and sensor coverage area provide regions of interest, processing constraints).

🎉感谢DL数据集的贡献
数据集信息
应用场景暂无
标注类型暂无
任务类型暂无
LicenseCustom
更新时间2020-12-31 17:24:21
数据概要
数据格式暂无
数据数量0
已标注数量0
文件大小6MB
版权归属方
Daimler AG
标注方
未知
了解更多和支持
立即开始构建AI
免费开始联系我们