2015年7月25日，微软亚洲研究院Tao Mei研究员应电子工程与信息科学系和多媒体计算与通信-教育部微软重点实验室的邀请在科大西区科技实验楼西楼1213会议室做题为《When Video Understanding Meets Deep Learning》的高水平学术前沿讲座。该讲座中，Tao Mei研究员深入地介绍了深度学习在视频理解方面的应用，并着重介绍了其研究组在基于深度学习的视频理解方面取得的研究成果，并与参会师生进行了深入的交流和探讨。Tao Mei研究员是我院兼职博导，与我院老师长期紧密合作，联合培养了多名优秀学。

　　图1 报告人：Tao Mei (Microsoft Research Asia)

　　图2 Tao Mei研究员做题为《When Video Understanding Meets Deep Learning》的报告。

　　报告摘要：The recent advances in deep learning have boosted the research on video analysis. For example, convolutional neural networks have demonstrated the superiority on modeling high-level visual concepts, while recurrent neural networks have been proven to be good at modeling mid-level temporal dynamics in the video data. We present a few recent advances for understanding video content using deep learning techniques. Specifically, this talk will focus on: 1) translating video to sentence with joint embedding and translation, which achieves the best to-date performance in this nascent vision task, 2) first-person video highlight extraction with a pairwise deep ranking model, and 3) action recognition with a multi-granular spatiotemporal architecture which achieved rank 2 in CVPR THUMOS 2015 video classification challenge.

　　报告人简介：Dr. Tao Mei is a Lead Researcher with Microsoft Research, Beijing, China. His current research interests include multimedia information retrieval and computer vision. He has authored or co-authored over 150 papers in journals and conferences and holds 13 U.S. granted patents. Tao was the recipient (together with his interns) of several paper awards from prestigious multimedia journals and conferences, including the IEEE T-CSVT Best Paper Award in 2014, the IEEE TMM Prize Paper Award in 2013, and the Best Paper Awards at ACM Multimedia in 2009 and 2007, etc. He is an Associate Editor of IEEE Trans. on Multimedia, Multimedia Systems, Neurocomputing, and the Communications of CCF. He is the General Co-chair of ACM ICIMCS 2013, the Program Co-chair of IEEE ICME 2015, IEEE MMSP 2015 and MMM 2013. He received the B.E. degree in automation and the Ph.D. degree in pattern recognition and intelligent systems from the University of Science and Technology of China, Hefei, China, in 2001 and 2006, respectively.