When 2D and 3D Scene Understanding Meets Deep Learning and Big Visual Data

Speaker: Dr. Dan XU
         Assistant Professor
         Department of Computer Science and Engineering
         HKUST

Title:  "When 2D and 3D Scene Understanding Meets Deep Learning and Big
         Visual Data"

Date:   Monday, 18 October 2021

Time:   4:00pm - 5:00pm

Venue:  Lecture Theater F (Leung Yat Sing Lecture Theater)
        (near lift 25/26, HKUST)

Zoom link:
https://hkust.zoom.us/j/95532049042?pwd=UjkvVG9oZEhqZ1A5M2NJbWplelRJQT09

Meeting ID:     955 3204 9042
Passcode:       CSE

**Note to CSE PGs with NIHK status, please attend the seminar via zoom**


Abstract:

In this talk, we will give a general introduction about 2D and 3D scene
understanding, and present how deep learning and big visual data have been
remarkably advancing the research and development of this domain. This may
involve several fundamental tasks in computer vision, including image
recognition, 2D/3D object detection, semantic segmentation, 3D
reconstruction, and visual SLAM. We will also show the generalization of
state-of-the-art 2D and 3D scene understanding techniques to challenging
real-life application scenarios, such as autonomous driving, robotic
navigation, and augmented/virtual reality (AR/VR).


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Biography:

Dr. Dan Xu is an Assistant Professor in the Department of Computer Science
and Engineering (CSE), Hong Kong University of Science and Technology
(HKUST). Before joining HKUST, he was a Postdoctoral researcher in the
Visual Geometry Group (VGG) at the University of Oxford, working with
Prof. Andrea Vedaldi and Prof. Andrew Zisserman. He received his Ph.D. in
Computer Science from the University of Trento in 2018, under the
supervision of Prof. Nicu Sebe. He was also a visiting Ph.D. student in
the MMLab at the Chinese University of Hong Kong (CUHK) under the
supervision of Prof. Xiaogang Wang.

His research mainly focuses on computer vision, multimedia, and deep
learning. Specifically, he is interested in multi-modal and structured
representation learning, statistical modelling within deep learning, as
well as their applications in 2D/3D scene understanding, involving topics
such as scene depth estimation, visual SLAM, object detection, and scene
parsing. He served as Senior Programme Committee (SPC) / Area Chair (AC)
at multiple international conferences including AAAI, ACM Multimedia, and
WACV. He received the Best Scientific Paper award at ICPR 2016 and a Best
Paper Nominee at ACM Multimedia 2018.