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Title: Visual Perception and Learning in an Open World
Speaker: Dr Shu KONG, Assistant Professor, Department of Computer Science and Engineering, Texas A&M University
Date: May 23, 2023
Time: 10:00am – 11:00am

Mode: Hybrid. Seats for on-site participants are limited. A confirmation email will be sent to participants who have successfully registered.


Visual perception is indispensable in numerous applications spanning autonomous vehicles and interdisciplinary research. Today’s visual perception algorithms are often developed under a closed-world paradigm, which assumes the data distribution and categorical labels are fixed a priori. This assumption is unrealistic in the real open world, which contains vast situations that are unpredictable and dynamic. As a result, closed-world visual perception systems appear to be brittle in the open-world. For example, equipped with such visual perception systems, an autonomous vehicle could fail to recognize a never-before-seen overturned truck and cause collision; it could fail to detect a pedestrian in a dark night and cause casualties. In this talk, I will present my solutions to recognizing unknown objects, segmenting and detecting general objects, and improving object detection using multimodal signals. If time allows, I will share my thought about open-world visual perception and learning, and sketch my future research.


Assistant Professor @ Department of Computer Science and Engineering, Texas A&M University
Shu Kong is on the faculty in the Department of Computer Science and Engineering, Texas A&M University, after postdoc training in the Robotics Institute, Carnegie Mellon University. He received the PhD degree in computer science from the University of California, Irvine. His research interests include computer vision, applied machine learning, and their broad applications. His current research focus is on visual perception and learning in the open world. His recent paper on this topic received honorable mention for Best Paper / Marr Prize at ICCV 2021. His latest interdisciplinary research develops high-throughput pollen analysis tools, which were featured by the National Science Foundation as that “open new era of fossil pollen research.”

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