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Caltech Pedestrian Detection Benchmark
创建来自Hello Dataset
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Overview

The Caltech Pedestrian Dataset consists of approximately 10 hours of 640x480 30Hz video taken from a vehicle driving through regular traffic in an urban environment. About 250, 000 frames (in 137 approximately minute long segments) with a total of 350,000 bounding boxes and 2300 unique pedestrians were annotated.

Data Annotation

The annotation includes temporal correspondence between bounding boxes and detailed occlusion labels. More information can be found in our PAMI 2012 and CVPR 2009 benchmarking papers.

Data Format

The training data (set00-set05) consists of six training sets (~1GB each), each with 6-13 one-minute long seq files, along with all annotation information (see the paper for details). The testing data (set06-set10) consists of five sets, again ~1GB each.

🎉感谢Hello Dataset的贡献
数据集信息
应用场景PersonAutonomous Driving
标注类型Box2D
任务类型暂无
LicenseUnknown
更新时间2021-03-24 22:51:55
数据概要
数据格式VideoImage
数据数量0
已标注数量0
文件大小11MB
版权归属方
Caltech Computer Vision Laboratory
标注方
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