JAAD

displayName: JAAD
license:
- MIT
paperUrl: https://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w3/Rasouli_Are_They_Going_ICCV_2017_paper.pdf
publishDate: "2017"
publishUrl: http://data.nvision2.eecs.yorku.ca/JAAD_dataset/
publisher:
- New York University
tags:
- Pedestrians
- Traffic lights
taskTypes:
- Object Detection

---
# 数据集介绍
## 简介
JAAD是在自动驾驶的背景下研究共同注意力的数据集。重点是过马路时的行人和驾驶员行为以及影响他们的因素。为此，JAAD数据集提供了从超过240小时的驾驶镜头中提取的346短视频剪辑 (5-10秒长) 的丰富注释集合。这些在北美和东欧的几个地点拍摄的视频代表了在各种天气条件下日常城市驾驶的典型场景。为所有行人提供了带有遮挡标签的边界框，使该数据集适合行人检测。行为注释为与驾驶员互动或需要驾驶员注意的行人指定了行为。对于每个视频，都有几个标签 (天气，位置等) 和固定列表中的带时间戳的行为标签 (例如，停止，行走，观看等)。此外，为每个行人提供人口统计属性列表 (例如年龄、性别、运动方向等) 以及每个帧的可见交通场景元素列表 (例如停车标志、交通信号等)。

## Download dataset
:modelscope-code[]{type="git"}

displayName: JAAD
license:
- MIT
paperUrl: https://openaccess.thecvf.com/content_ICCV_2017_workshops/papers/w3/Rasouli_Are_They_Going_ICCV_2017_paper.pdf
publishDate: "2017"
publishUrl: http://data.nvision2.eecs.yorku.ca/JAAD_dataset/
publisher:
- New York University
tags:
- Pedestrians
- Traffic lights
taskTypes:
- Object Detection

---
# Dataset Introduction
## Introduction
JAAD is a dataset for studying joint attention in the context of autonomous driving. The focus is on pedestrian and driver behaviors when crossing roads and the factors influencing them. To this end, the JAAD dataset provides a richly annotated collection of 346 short video clips (5–10 seconds in length) extracted from over 240 hours of driving footage. Filmed at several locations across North America and Eastern Europe, these videos represent typical scenarios of daily urban driving under various weather conditions. Bounding boxes with occlusion labels are provided for all pedestrians, making this dataset suitable for pedestrian detection. Behavior annotations specify behaviors for pedestrians that interact with drivers or require driver attention. For each video, there are several labels (weather, location, etc.) and timestamped behavior labels from a fixed list (e.g., stopping, walking, looking, etc.). Additionally, a list of demographic attributes (e.g., age, gender, movement direction, etc.) for each pedestrian and a list of visible traffic scene elements (e.g., stop signs, traffic signals, etc.) for each frame are provided.

## Download Dataset
:modelscope-code[]{type="git"}

搜集汇总

背景与挑战

背景概述

JAAD是一个专注于自动驾驶中联合注意力研究的数据集，包含346个短视频片段，涵盖多种天气和城市驾驶场景，提供丰富的行人行为、遮挡标签及交通场景元素注释。