VMMRdb

The Vehicle Make and Model Recognition dataset (VMMRdb) is large in scale and diversity, containing 9,170 classes consisting of 291,752 images, covering models manufactured between 1950 and 2016. VMMRdb dataset contains images that were taken by different users, different imaging devices, and multiple view angles, ensuring a wide range of variations to account for various scenarios that could be encountered in a real-life scenario. The cars are not well aligned, and some images contain irrelevant background. The data covers vehicles from 712 areas covering all 412 sub-domains corresponding to US metro areas. Our dataset can be used as a baseline for training a robust model in several real-life scenarios for traffic surveillance.

车辆品牌与型号识别数据集（Vehicle Make and Model Recognition Dataset, VMMRdb）规模庞大且样本多样性丰富，共包含9170个类别、291752张图像，涵盖1950年至2016年间生产的各类车辆型号。该数据集收录的图像由不同用户使用多种成像设备拍摄，且涵盖多种拍摄视角，由此生成丰富的样本变异类型，可覆盖真实场景中可能遭遇的各类应用情境。图像中的车辆未经过精准对齐，部分样本还存在无关背景干扰。数据集的样本覆盖712个区域，涵盖对应美国都会区的全部412个子区域。本数据集可作为训练鲁棒性交通监控模型的基准数据集，适用于交通监控领域的多种真实应用场景。

搜集汇总

背景与挑战

背景概述

VMMRdb是一个大规模的车辆品牌和型号识别数据集，包含9,170个类别和291,752张图像，覆盖1950年至2016年的车型。数据集具有多样化的图像来源和视角，适用于交通监控等实际场景的模型训练。