2017/11/24 (五) 14:20 Prof. 邱維辰（交通大學資工系）Introduction to Deep Generative Models and Recent Results on Cross-Domain Disentanglement
Topic：Introduction to Deep Generative Models and Recent Results on Cross-Domain Disentanglement(English)
Date&Time：2017/11/24(五) 14:20
Speaker：邱維辰 教授 (交通大學 資工系)
Location：清華大學台達館 DELTA @R216
Abstract:
In this talk, I will give a brief introduction for the deep generative models which brings another leap for deep learning society, and also present our recent results on deep cross-domain disentanglement, cross-resolution face recognition, and sketch-to-photo face inversion. The underlying idea is to not only learn the generative process of individual domain, but also explore the common latent space of different domain data and discover how they are related over there.
Bio:
Wei-Chen Chiu (邱維辰) received the B.S. degree in Electrical Engineering and Computer Science and the M.S. degree in Computer Science from National Chiao Tung University in, Hsinchu, Taiwan in 2008 and 2009. He further received Doctor of Engineering Science (Dr.-Ing.) from Max Planck Institute for Informatics, Saarbrucken, Germany, in 2016.
He is an assistant professor in Department of Computer Science, National Chiao Tung University and director of EVA Lab from August 2017. He was an postdoctoral researcher in Research Center for Information Technology Innovation, Academia Sinica, from Feb. to July. 2017, and a research scientist in a Taiwanese startup, Viscovery, from Aug. 2016 to Jan. 2017. His current research interests generally include computer vision, machine learning, and deep learning, with special focus on generative models.
Date&Time：2017/11/24(五) 14:20
Speaker：邱維辰 教授 (交通大學 資工系)
Location：清華大學台達館 DELTA @R216
Abstract:
In this talk, I will give a brief introduction for the deep generative models which brings another leap for deep learning society, and also present our recent results on deep cross-domain disentanglement, cross-resolution face recognition, and sketch-to-photo face inversion. The underlying idea is to not only learn the generative process of individual domain, but also explore the common latent space of different domain data and discover how they are related over there.
Bio:
Wei-Chen Chiu (邱維辰) received the B.S. degree in Electrical Engineering and Computer Science and the M.S. degree in Computer Science from National Chiao Tung University in, Hsinchu, Taiwan in 2008 and 2009. He further received Doctor of Engineering Science (Dr.-Ing.) from Max Planck Institute for Informatics, Saarbrucken, Germany, in 2016.
He is an assistant professor in Department of Computer Science, National Chiao Tung University and director of EVA Lab from August 2017. He was an postdoctoral researcher in Research Center for Information Technology Innovation, Academia Sinica, from Feb. to July. 2017, and a research scientist in a Taiwanese startup, Viscovery, from Aug. 2016 to Jan. 2017. His current research interests generally include computer vision, machine learning, and deep learning, with special focus on generative models.