Video Understanding Meets Deep Learning

Date:           Thursday, 19 Nov 2015
Time:           10:00am - 12 noon
Venue:          Lecture Theater G (near lifts 25/26), HKUST


(Seminar II)

Speaker:        Dr. Tao MEI
                Lead Researcher
                Microsoft Research Asia

Title:          "Video Understanding Meets Deep Learning"

Time:           11:00am to 12 noon


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.


Dr. Tao Mei is a Lead Researcher with Microsoft Research, Beijing, China.
His current research interests include multimedia information retrieval
and computer vision (video analytics). He has authored or co-authored over
100 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,