Recent Advances on Application of Deep Learning for Recovering Object Pose
Li, Wanyi1; Luo, Yongkang1; Wang, Peng1; Qin, Zhengke1; Zhou, Hai2; Qiao, Hong3
2016-12
会议名称IEEE International Conference on Robotics and Biomimetics
会议录名称IEEE International Conference on Robotics and Biomimetics
会议日期Dec. 3 – Dec. 7, 2016
会议地点Qingdao, China
摘要Recovering object pose is of great importance to many higher level tasks such as robotic manipulation, scene understanding and augmented reality to name a few. Following the recent major breakthroughs in many computer vision tasks made by the deep learning, intensive research to experiment with it also in the task of recovering object pose is conducting. This paper aims to review the state-of-the-art progress on deep learning based pose estimation methods. Firstly, we introduce some popular datasets together with their relevant attributes. Secondly, the deep learning based pose estimation methods are summarized and categorized, and detailed descriptions of representative methods are provided, and their pros and cons are examined. Thirdly, evaluation protocol and comparable performance of reviewed approaches are given. Finally, we highlight the advantages of deep learning based pose estimation methods and provide insights for future.
关键词Pose Estimation Deep Learning Survey
收录类别EI
语种英语
文献类型会议论文
条目标识符http://ir.ia.ac.cn/handle/173211/12113
专题精密感知与控制研究中心_精密感知与控制
通讯作者Li, Wanyi
作者单位1.Research Center of Precision Sensing and Control, Institute of Automation, Chinese Academy of Sciences
2.Research Center of Laser Fusion, China Academy of Engineering Physics
3.State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences
推荐引用方式
GB/T 7714
Li, Wanyi,Luo, Yongkang,Wang, Peng,et al. Recent Advances on Application of Deep Learning for Recovering Object Pose[C],2016.
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