[Theory] NOW: 5/3 TTIC Distinguished Lecture Series: David Forsyth, UIUC

[Brandie Jones]

*When:    * Wednesday, May 3rd at *11:30 AM CT*



*Where:    *Talk will be given *live, in-person* at

                     TTIC, 6045 S. Kenwood Avenue

                     5th Floor, Room 530


*Virtually:  *  via Panopto* (Livestream
<https://uchicago.hosted.panopto.com/Panopto/Pages/Viewer.aspx?id=60b3f587-be8f-428a-8706-afbd012ab9bc>)
*



*Who:         *Prof. David Forsyth, UIUC

*Title:         *Intrinsic images, lighting, and relighting without any
labelling

*Abstract:   *Intrinsic images are maps of surface properties. A classical
problem
is to recover an intrinsic image, typically a map of surface lightness,
from an image.   The topic has mostly dropped from view, likely for three
reasons: training data is mostly synthetic; evaluation is somewhat
uncertain; and clear applications for the resulting albedo are missing.
The decline of this topic has a consequence - mostly, we don't understand
and can't mitigate the effects of lighting.

I will show the results of simple experiments that suggest that very good
modern depth and normal predictors are strongly sensitive to lighting -- if
you relight a scene in a reasonable way, the reported depth will change.
This is intolerable. To fix this problem, we need to be able to produce
many different lightings of the same scene.   I will describe a method to
do so.  First, one learns a method to estimate albedo from images without
any labelled training data (which turns out to perform well under
traditional evaluations).  Then, one forces an image generator to produce
many different images that have the same albedo -- with care, these are
relightings of the same scene.  Finally, a GAN inverter allows us to apply
the process to real images.  I will show some interim results suggesting
that learned relightings might genuinely improve estimates of depth,
normal and albedo.

Bio:     I am currently Fulton-Watson-Copp chair in computer science at
 U. Illinois at Urbana-Champaign, where I moved from U.C Berkeley, where I
was also a full professor.  I have occupied the Fulton-Watson-Copp chair in
Computer Science at the University of Illinois since 2014. I have published
over 170 papers on computer vision, computer graphics and machine learning.
I have served as program co-chair or general co-chair for vision
conferences on many occasions. I received an IEEE
 technical achievement award in 2005 for my research.  I became an IEEE
Fellow in 2009, and an ACM Fellow in 2014.  My textbook, "Computer Vision:
A Modern Approach" (joint with J. Ponce and published by Prentice Hall) was
widely adopted as a course text. My recent textbook, “Probability and
Statistics for Computer Science”, is in the top quartile of Springer
computer science chapter downloads.  A further textbook “Applied Machine
Learning” has just appeared in print. I have served two terms as Editor of
Chief, IEEE TPAMI. I serve on a number of scientific advisory boards.

Hos*t: Greg  <greg at ttic.edu>**Shakhnarovich* <greg at ttic.edu>



-- 
*Brandie Jones *
*Executive **Administrative Assistant*
Toyota Technological Institute
6045 S. Kenwood Avenue
Chicago, IL  60637
www.ttic.edu
Working Remotely on Tuesdays
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