Content Gazette - August 2020 - 4

About the Presenter:
Jong Chul Ye is a Professor at the Dept. of Bio/Brain Engineering and Adjunct Professor at the

Dept. of Mathematical Sciences of Korea Advanced Institute of Science and Technology (KAIST),

Korea. He received the B.Sc. and M.Sc. degrees from Seoul National University, Korea, and the
Ph.D. degree from Purdue University, West Lafayette, IN. Before joining KAIST, he was a Senior

Researcher at Philips Research, GE Global Research in New York, and a postdoctoral fellow at
University of Illinois at Urbana Champaign. He has served as an associate editor of IEEE Trans. on

Image Processing, IEEE Trans. on Computational Imaging, and an editorial board member for
Magnetic Resonance in Medicine. He is currently an associate editor for IEEE Trans. on Medical

Imaging, and a Senior Editor of IEEE Signal Processing Magazine. He is an IEEE Fellow, Chair of
IEEE SPS Computational Imaging TC, and IEEE EMBS Distinguished Lecturer. He was a General

Co-chair for 2020 IEEE Symp. On Biomedical Imaging (ISBI) (with Mathews Jacob), and will be a
Program Co-Chair for 2024 IEEE

International Conference on Acoustics, Speech, and Signal

Processing, Seoul. His group was the first winner of the
2009 Recon Challenge at the ISMRM Workshop with k-t

FOCUSS algorithm, and the runner-up at 2016 Low Dose
CT

Grand

Challenge

organized

by

the

American

Association of Physicists in Medicine (AAPM) with the
world's first deep learning algorithm for low-dose CT
reconstruction. His current research interests focus is deep
learning

theory

reconstruction

and

algorithms

problems

in

ultrasound, remote sensing, etc.

for

x-ray

various

CT,

MRI,

imaging
optics,

Date: 28 July 2020

Speaker: Orazio Gallo, Nvidia

Title: Depth Estimation from RGB Images with Applications to Novel View Synthesis and
Autonomous Navigation.

Abstract: Depth information is a central requirement for many computer vision and computational
imaging applications. A number of sensors exist that can capture depth directly. Standard RGB

cameras offer a particularly attractive alternative thanks to their lower price point and widespread

availability, but they also introduce new challenges. In this talk I will address two of their main
challenges.

The first challenge is dynamic content. When a scene is captured with a monocular camera,
moving objects break the epipolar constraints, thus making it impossible to directly estimate depth. I
will describe a method to address this issue while also improving the quality of the depth estimation

in the static regions of the scene. I will then use the resulting depth to synthesize novel views of the
scene or to create effects like the bullet-time effect, but without the need for synchronized cameras.

The issue of dynamic content can also be addressed by using multiple cameras simultaneously, as
is the case of stereo. However, while state-of-the-art, deep-learning stereo algorithms produce

www.signalprocessingsociety.org

[4]

AUGUST 2020


http://www.B.Sc http://www.M.Sc http://www.signalprocessingsociety.org

Content Gazette - August 2020

Table of Contents for the Digital Edition of Content Gazette - August 2020

Content Gazette - August 2020 - Cover1
Content Gazette - August 2020 - Cover2
Content Gazette - August 2020 - 1
Content Gazette - August 2020 - 2
Content Gazette - August 2020 - 3
Content Gazette - August 2020 - 4
Content Gazette - August 2020 - 5
Content Gazette - August 2020 - 6
Content Gazette - August 2020 - 7
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Content Gazette - August 2020 - 27
Content Gazette - August 2020 - 28
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Content Gazette - August 2020 - 38
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Content Gazette - August 2020 - 40
Content Gazette - August 2020 - 41
Content Gazette - August 2020 - 42
Content Gazette - August 2020 - Cover3
Content Gazette - August 2020 - Cover4
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