原文：
CORe50, specifically designed for (C)ontinual (O)bject (Re)cognition, is a collection of 50 domestic objects belonging to 10 categories: plug adapters, mobile phones, scissors, light bulbs, cans, glasses, balls, markers, cups and remote controls. Classification can be performed at object level (50 classes) or at category level (10 classes). The first task (the default one) is much more challenging because objects of the same category are very difficult to be distinguished under certain poses.
The dataset has been collected in 11 distinct sessions (8 indoor and 3 outdoor) characterized by different backgrounds and lighting. For each session and for each object, a 15 seconds video (at 20 fps) has been recorded with a Kinect 2.0 sensor delivering 300 RGB-D frames.
Objects are hand hold by the operator and the camera point-of-view is that of the operator eyes. The operator is required to extend his arm and smoothly move/rotate the object in front of the camera. A subjective point-of-view with objects at grab-distance is well-suited for a number of robotic applications. The grabbing hand (left or right) changes throughout the sessions and relevant object occlusions are often produced by the hand itself.
译：
CORe50是专门为（C）连续性（O）物体（Re）认知而设计的，是一个集合了50个家庭物品，属于10个类别：插头适配器、手机、剪刀、灯泡、罐子、眼镜、球、马克笔、杯子和遥控器。分类可以在对象级别（50个类）或类别级别（10个类）执行。第一个任务（默认任务）更具挑战性，因为在某些姿势下，同一类别的对象很难区分。
数据集收集了11个不同的会议（8个室内和3个室外）的特点是不同的背景和照明。对于每个会话和每个对象，一段15秒的视频（每秒20帧）都是用Kinect 2.0传感器录制的，可传送300 RGB-D帧。
操作人员手持物体，摄像机视角为操作员眼睛视角。要求操作者伸出手臂，平稳地移动/旋转摄像机前面的物体。物体处于抓取距离时的主观观点非常适合机器人应用。抓取手（左或右）在整个治疗过程中发生变化，相关的物体遮挡通常由手本身产生。
大家可以到官网地址下载数据集，我自己也在百度网盘分享了一份。可关注本人公众号，回复“2020100701”获取下载链接。
注意：
下面那个文档，我用压缩工具“winrara”进行了切分，到时下载回来后，可以用工具合并。可参考以下文章。https://blog.csdn.net/ispeasant/article/details/108894004
