Plenary Talks

Plenary Talk 1

Title : Deep Learning meets Reconstruction and SLAM
Date : 20-12-2016
Time : 9:30 AM - 10:30 AM

Bio: Ian Reid is a Professor of Computer Science and an ARC Australian Laureate Fellow at the University of Adelaide. Until 2012 he was a Professor of Engineering Science at the University of Oxford. He received a BSc in Computer Science and Mathematics with first class honours from University of Western Australia in 1987 and was awarded a Rhodes Scholarship in 1988 to study at the University of Oxford, where he obtained a D.Phil. in 1992 and stayed initially as a postdoctoral researcher, and latterly as a University Lecturer. His research interests include active vision, visual tracking, SLAM, human motion capture and intelligent visual surveillance, with an emphasis on real-time implementations whenever possible. He has published 180 articles and has an h-index of 55. His work won prizes at BMVC '05, '09, '10, and CVPR '08 and 3DV '14. He serves on the program committees of various national and international conferences. He is also on the editorial board of IEEE T-PAMI and Computer Vision and Image Understanding.

Deep Learning meets Reconstruction and SLAM

Abstract :Deep Learning has rapidly and irrevocably changed the way numerous tasks in computer vision are carried out. In particular it has opened the door to useful semantic interpretations of scenes. In this talk I will discuss ongoing work in my group in which we are using deep learning in the context Simultaneous Localisation and Mapping. I will discuss how we generate semantically useful segmentations of scenes, and how we estimate the depth of a scene from a single view, trained without supervision. I will show how we have incorporated some of these ideas into a real-time Dense SLAM system.

Plenary Talk II

Title : Beyond Indian Language OCRs: Problems that Beckon in the Era of Deep Learning
Date : 21-12-2016
Time : 9:00 AM - 10:00 AM

Bio: C. V. Jawahar is a professor at IIIT Hyderabad, India. He received his PhD from IIT Kharagpur and has been with IIIT Hyderabad since Dec. 2000. At IIIT Hyderabad, Jawahar leads a group focusing on computer vision, machine learning and multimedia systems. In the recent years, he has been looking into a set of problems that overlap with vision, language and text. He is also interested in large scale multimedia systems with special focus on retrieval. He has more than 50 publications in top tier conferences in computer vision, robotics and document image processing. He has served as a chair for previous editions of ACCV, WACV, IJCAI and ICVGIP. Presently, he is an area editor of CVIU and an associate editor of IEEE PAMI. He is also a program co-chair for ICDAR 2017 and ACCV 2018.

Beyond Indian Language OCRs: Problems that Beckon in the Era of Deep Learning

Abstract : What is the state of the art in Indian language OCRs? What are the left out problems? How do we catch up with English? Is language the (only) barrier? In this talk, I discuss a set of problems that relate to the text in images (such as printed, handwritten and natural scenes). Text is a semantically useful cue for image understanding. Automatically understanding text can also help in bridging the gap between the text/language processing, and understanding these images. Focus of the talk is primarily on problems that overlaps with language, learning and vision. The talk centers around our recent and ongoing attempts in this space.

Plenary Talk III

Title : Blind Dynamic Scene Deblurring Techniques
Date : 22-12-2016
Time : 9:00 AM - 10:00 AM

Bio: Kyoung Mu Lee received the B.S. and M.S. Degrees in Control and Instrumentation Eng. from Seoul National University, Seoul, Korea in 1984 and 1986, respectively, and Ph. D. degree in Electrical Engineering from the University of Southern California in 1993. He is currently with the Dept. of ECE at Seoul National University as a professor. His primary research interests include scene understanding, object recognition, low-level vision, visual tracking, and visual navigation. He is currently serving as an AEIC (Associate Editor in Chief) of the IEEE TPAMI, an Area Editor of the Computer Vision and Image Understanding (CVIU), and has served as an Associate Editor of the IEEE TPAMI, the Machine Vision Application (MVA) Journal and the IPSJ Transactions on Computer Vision and Applications (CVA), and the IEEE Signal Processing Letter. He also has served as Area Chairs of CVPR, ICCV, and ECCV many times. He was a Distinguished Lecturer of the Asia-Pacific Signal and Information Processing Association (APSIPA) for 2012-2013. He will serve as a General Co-Chair of ACM MM2018, ACCV2018 and ICCV2019. More information can be found on his homepage

Blind Dynamic Scene Deblurring Techniques

Abstract : Deblurring of images and videos of dynamic scene is one of the important and fundamental problems in image processing and computer vision. In this talk, recent trends of deblurring techniques will be addressed, and a novel parametric model-based blind deblurring method that can cope with general blurs inherent in dynamic scenes will be introduced. To handle locally varying blurs caused by various sources, such as camera shake, moving objects, and depth variation in dynamic scenes, a simple yet powerful bidirectional optical flow model is proposed for the approximation of the pixel-wise blur kernel. With this model, the problem is casted into an energy minimization framework, and then the latent images are recovered through the minimization of the energy function. Empirical results will demonstrate how the new approach advances the state-of-the-art performance in real and challenging scenarios.

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