I would like to invite you to attend this week's CSCE 791 seminar. These seminars highlight research being performed in our department and across the world. All CSCE 791 seminars are open to anybody who wishes to attend - not just students registered for the course.
Speaker: Song Wang, University of South Carolina
Abstract: Most existing methods of human attribute recognition are part-based and the performance of these methods is highly dependent on the accuracy of body-part detection, which is a well known challenging problem in computer vision. In this talk, I will introduce a new method to recognize human attributes by using CAM (Class Activation Map) network, as well as an unsupervised algorithm to refine the attention heat map, which is an intermediate result in CAM and reflects relevant image regions for each attribute. The proposed method does not require the detection of body parts and the prior correspondence between body parts and attributes. The proposed methods can achieve comparable performance of attribute recognition to the current state-of-the-art methods.
Bio: Song Wang received the Ph.D. degree in electrical and computer engineering from the University of Illinois at Urbana–Champaign in 2002. He received his M.E. and B.E. degrees from Tsinghua University in 1998 and 1994, respectively. In 2002, he joined the Department of Computer Science and Engineering in University of South Carolina, where he is currently a Professor and the director of the Computer Vision Lab. His current research interest is focused on computer vision, image processing and machine learning, as well as their applications to materials science, medical imaging, digital humanities and archaeology. He has published more than 100 research papers in journal and conferences, including top venues like CVPR, ICCV, NIPS, IJCAI, TPAMI, IJCV and TIP. He is currently serving as the Publicity/Web Portal Chair of the Technical Committee of Pattern Analysis and Machine Intelligence of the IEEE Computer Society, and an Associate Editor of Pattern Recognition Letters. He is a senior member of IEEE.