DTLD

DTLD contains more than 230,000 annotated traffic lights in camera images with a resolution of 2 megapixels. The dataset was recorded in 11 cities in Germany with a frequency of 15 Hz. Due to additional annotation attributes such as the traffic light pictogram, orientation or relevancy 344 unique classes exist. In addition to camera images and labels we provide stereo information in form of disparity images allowing stereo-based detection and depth-dependent evaluations. Our sophisticated labeling tool allows to annotate traffic lights down to a width of 5 pixels or below. Therefore DTLD consists of a high number of very small objects (Figure 2). This makes the dataset also predestined for researchers working on small object detection. By also annotating traffic lights consisting of one, two (e.g. pedestrian traffic lights) or four light units (e.g. bus/tram traffic lights) DTLD has a higher aspect ratio variance than other datasets. One important property of DTLD is its high regional variance (Figure 4), i.e. the distribution of the labels in the 2D image. This was reached by only adding non-static scenes to the dataset. Only static scenes, in which at least one traffic light state changes are added. Dataset statistics

DTLD数据集包含超过23万张带有标注交通信号灯的相机图像，图像分辨率为2兆像素（2 megapixels）。该数据集采集自德国11座城市，采集频率为15赫兹（15 Hz）。由于包含交通灯象形图、朝向、相关性等额外标注属性，该数据集共存在344个唯一类别。
除相机图像与标注标签外，我们还提供视差图像形式的立体信息，可用于基于立体视觉的检测任务与深度相关评估。我们开发的高精度标注工具可对宽度仅为5像素及以下的交通信号灯进行标注，因此DTLD包含大量超小目标（见图2），使其非常适合致力于超小目标检测研究的科研人员。
此外，该数据集还对包含1个、2个（如行人信号灯）或4个灯组（如公交/有轨电车信号灯）的交通信号灯进行了标注，因此其宽高比变化范围大于其他同类数据集。DTLD的一项重要特性是其高度的区域差异性（见图4），即标签在二维图像中的分布情况。这一特性通过仅向数据集中添加非静态场景实现，即仅添加包含至少一个交通灯状态变化的场景。
数据集统计信息

搜集汇总

背景与挑战

背景概述

DTLD是一个包含超过23万标注交通灯图像的大规模数据集，分辨率高达200万像素，覆盖德国11个城市。数据集特色包括丰富的标注属性（344个独特类别）、立体信息支持，以及特别适合小物体检测研究的高比例微小交通灯对象。