CityFlow

Data for this challenge comes from multiple traffic cameras from a city in the United States as well as from state highways in Iowa. Specifically, we have time-synchronized video feeds from several traffic cameras spanning major travel arteries of the city. Most of these feeds are high resolution 1080p feeds at 10 frames per second. The vantage point of these cameras is for traffic and transportation purposes and the data will be redacted in terms of faces and license plates to address data privacy issues. Moreover, we have built a synthetic vehicle data set consisting of over 1,300 distinct vehicles and over 140,000 images. These synthetic images will form an augmented training set to be used along with the real-world traffic data set for Tracks 2 and 3.

本挑战赛所用数据集源自美国某城市的多台交通摄像头以及爱荷华州的州级公路监控设备。具体而言，我们获取了覆盖该市主要交通干道的多台交通摄像头的时间同步视频流。其中大部分视频流为1080p高分辨率规格，帧率为10帧每秒。这些摄像头的布设视角均服务于交通与运输监测需求，且为保障数据隐私，已对人脸及车牌信息进行脱敏处理。此外，我们还构建了包含1300余种不同车辆、总计14万余张图像的合成车辆数据集。该合成图像集将作为增强训练集，与真实交通数据集一同用于赛道2与赛道3的模型训练任务。

搜集汇总

背景与挑战

背景概述

CityFlow数据集是一个包含多源交通摄像头视频和合成车辆数据的集合，主要用于车辆计数、多摄像头车辆跟踪和车辆重新识别任务。数据集涵盖了城市交叉口、高速公路等多种交通场景，并包含不同光照和天气条件下的视频数据。