TICaM

TICaM是由德国人工智能研究中心创建的用于车辆内部监控的数据集，使用单一宽角度深度相机进行数据采集。该数据集包含6.7K真实时间飞行深度图像和3.3K合成图像，提供2D和3D对象检测、实例和语义分割以及活动标注。数据集旨在解决现有车内舱数据集在标注类别、记录场景和提供标注方面的不足，适用于训练车内监控系统和评估域适应方法。TICaM is an in-vehicle monitoring dataset developed by the German Research Center for Artificial Intelligence (DFKI), with data collected using a single wide-angle depth camera. The dataset contains 6.7K real-world Time-of-Flight (ToF) depth images and 3.3K synthetic images, and provides annotations for 2D and 3D object detection, instance and semantic segmentation, as well as activity annotation. This dataset aims to address the shortcomings of existing in-vehicle cabin datasets in terms of annotation categories, recorded scenarios and annotation provision, and is suitable for training in-vehicle monitoring systems and evaluating domain adaptation methods.

搜集汇总

背景与挑战

背景概述

TICaM是一个由德国人工智能研究中心开发的车辆内部监控数据集，包含6.7K真实深度图像和3.3K合成图像，提供多类标注如2D/3D检测和分割。该数据集旨在弥补现有车内舱数据集的不足，适用于训练监控系统和评估域适应方法。