Recent Advances on Application of Deep Learning for Recovering Object Pose

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	Recent Advances on Application of Deep Learning for Recovering Object Pose
	Li, Wanyi1 ; Luo, Yongkang1 ; Wang, Peng1 ; Qin, Zhengke 1; Zhou, Hai 2; Qiao, Hong3
	2016-12
会议日期	Dec. 3 – Dec. 7, 2016
会议地点	Qingdao, China
关键词	Pose Estimation Deep Learning Survey
英文摘要	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.
会议录	IEEE International Conference on Robotics and Biomimetics
语种	英语
内容类型	会议论文
源URL	[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]. 见:. Qingdao, China. Dec. 3 – Dec. 7, 2016.