IOTSC Talk Series: “ILL-Posed” Computer Vision Tasks
Dear Colleagues and Students,
The State Key Laboratory of Internet of Things for Smart City would like to invite you to join our “IOTSC Talk Series” on 18/01/2024 (Thursday). We are pleased to invite Prof. Xiaochun CAO from Sun Yat-Sen University as the speaker.
“ILL-Posed” Computer Vision Tasks
Speaker: Prof. Xiaochun CAO, Professor and Dean from School of Cyber Science and Technology, Sun Yat-Sen University
Date: 18/01/2024 (Thursday)
Time: 10:00 – 11:00
Language: English
Venue: N21-5005
Abstract:
Computer vision tasks range from the simple perspective projection matrix estimation in a traditional camera calibration application to the large-scale foundation model fitting in a contemporary object detection cloud service. One may solve most computer vision tasks through fitting functions mapping the dense, if not continuous due to quantization, visual input to a discrete and meaningful output space, including categories, bounding boxes, and depths. Due to the significant difference in cardinalities of the domain and codomain, these mapping functions fail to meet one of the three Hadamard criteria for being well-posed. In other words, the unstable computer vision solution does not depend continuously on the parameters or input data. Many researchers are trying their best to design or learn computer vision algorithms being sufficiently robust to complex perturbations such as occlusion, smoke, rain, and fog. There are also scholars looking for dedicated but powerful adversarial perturbations. Does there exist an invariant backdoor perturbation that is capable to push an arbitrary image across the decision boundary in a classification task? Are all perturbations adversarial? In this talk, I will introduce these questions our team is exploring and briefly outline some of the progress. However, much still remains unclear in spite of our efforts, and we reiterate that there might not have the answers we’re looking for before AI undergoes a brand new paradigm.
Speaker’s Bio:
Dr. Xiaochun CAO is a Professor and Dean of School of Cyber Science and Technology, Shenzhen Campus of Sun Yat-sen University. He received the B.E. and M.E. degrees both in computer science from Beihang University (BUAA), China, and the Ph.D. degree in computer science from the University of Central Florida, USA, with his dissertation nominated for the university level Outstanding Dissertation Award. After graduation, he spent about three years at ObjectVideo Inc. as a Research Scientist. From 2008 to 2012, he was a professor at Tianjin University. Before joining SYSU, he was a professor at Institute of Information Engineering, Chinese Academy of Sciences. He has authored and coauthored over 200 journal and conference papers. In 2004 and 2010, he was the recipients of the Piero Zamperoni best student paper award at the International Conference on Pattern Recognition. He is on the editorial boards of IEEE Transactions on Pattern Analysis and Machine Intelligence and IEEE Transactions on Image Processing, and was on the editorial boards of IEEE Transactions on Circuits and Systems for Video Technology and IEEE Transactions on Multimedia.
For enquiries: Tel: 8822 9141
Email: shirleyfong@um.edu.mo
Best Regards,
State Key Laboratory of Internet of Things for Smart City