Institute of Information Science, Academia Sinica

In recent years, deep reinforcement learning has been developed as one of the basic techniques in machine learning and successfully applied to a wide range of computer vision tasks (showing state-of-the-art performance). In this talk, I will introduce some deep reinforcement learning techniques and their applications in different visual content understanding tasks such as face recognition, action recognition, visual tracking, image search, and network compression. Lastly, I will discuss some open problems in deep reinforcement learning to show how to further develop more advanced algorithms for visual content understanding in the future.

Jiwen Lu received the B.Eng. degree in mechanical engineering and the M.Eng. degree in electrical engineering from the Xi’an University of Technology, Xi’an, China, in 2003 and 2006, respectively, and the Ph.D. degree in electrical engineering from Nanyang Technological University, Singapore, in 2012. He is currently an Associate Professor with the Department of Automation, Tsinghua University, Beijing, China. His current research interests include computer vision, pattern recognition, machine learning, and intelligent robotics. He has authored/co-authored over 200 scientific papers in these areas, where over 70 of them are IEEE Transactions papers (including 13 T-PAMI papers) and 53 of them are CVPR/ICCV/ECCV papers. He is a member of the Multimedia Signal Processing Technical Committee and the Information Forensics and Security Technical Committee of the IEEE Signal Processing Society and the Multimedia Systems and Applications Technical Committee and the Visual Signal Processing and Communications Technical Committee of the IEEE Circuits and Systems Society. He serves as the Co-Editor-of-Chief for the Pattern Recognition Letters, an Associate Editor for the IEEE Transactions on Image Processing, IEEE Transactions on Circuits and Systems for Video Technology, the IEEE Transactions on Biometrics, Behavior, and Identity Science, and Pattern Recognition. He was a recipient of the National 1000 Young Talents Program of China in 2015 and the National Science Fund of China for Excellent Young Scholars in 2018. He is a senior member of the IEEE.