报告1：《Learning-based Light Field Image Processing》
The light field (LF) image not only records the accumulated light intensity of the scene, but also implicitly encodes the three-dimensional geometry information of the scene. LF images facilitate/allow a wide range of interesting applications, e.g., image editing/post-capture refocus, 3-D reconstruction, etc. Moreover, the LF is considered as a promising paradigm for immersive 3-D telepresence, which can be widely applied to entertainment, telerehabilitation, business, etc., to significantly reform human work and life styles. Recent advances in commercial hand-held LF cameras make the convenient acquisition of LF images in a single snapshot possible, which dramatically boosts LF-based research and applications. In this talk, I will introduce our recent progress on learning-based LF image processing, including LF image denoising/compression/depth estimation, and high-fidelity LF image reconstruction (spatial/angular super-resolution)
Junhui Hou （侯军辉） has been an Assistant Professor with the Department of Computer Science, City University of Hong Kong since 2017. He received the Ph.D. degree in electrical and electronic engineering, Nanyang Technological University, Singapore, in 2016. His research interests include image/geometry processing and analysis, semi-supervised learning, and data compression and adaptive transmission. Dr. Hou was the recipient of the Chinese Government Award for Outstanding Students Study Abroad in 2015, and the Early Career Award from the Hong Kong Research Grants Council in 2018. He serves/served as an Associate Editor for The Visual Computer, an Area Editor for Signal Processing: Image Communication, and the Guest Editor for the JVCIR and IEEE JSTARS. He is/was an Area Chair of ACM MM’19 and IEEE ICME’20.
报告2：《Medical Image Analysis for Automated Glaucoma Screening》
Glaucoma is the second leading cause of blindness world-wide (only second to cataracts), as well as the foremost cause of irreversible blindness. Since vision loss from glaucoma cannot be reversed, early screening and detection methods are essential to preserve vision and life quality. For wide-scale screening, automated glaucoma screening methods are needed. In this talk, I will introduce several our recent works for glaucoma screening in both retinal fundus image and Anterior Segment Optical Coherence Tomography (AS-OCT), including: optic disc and cup segmentation in fundus image, ensemble network for glaucoma detection, automated AS-OCT structure segmentation, measurement, and screening, etc..
Huazhu Fu （付华柱） is the Senior Scientist with the Inception Institute of Artificial Intelligence (IIAI), Abu Dhabi, United Arab Emirates. He received the Ph.D. degree from Tianjin University, China, in 2013, and then worked as the research fellow at Nanyang Technological University (NTU), Singapore for two years. From 2015 to 2018, he worked as a Research Scientist with the Agency for Science, Technology and Research (A*STAR), Singapore. His research includes computer vision, image processing, and medical image analysis. He is the Associate Editor of IEEE Access and BMC Medical Imaging, and the Guest Editor of IEEE Journal of Biomedical and Health Informatics.