[Colloquium] [CS] TODAY 2pm: Stella Yu (UC Berkeley) - Learning Mid-Level Vision from Natural Data

[Rob Mitchum]

*Data Science Institute/Computer Science Seminar*

*Stella Yu*
*Director of Vision Group, International Computer Science Institute*

*Senior Fellow, Berkeley Institute for Data Science*
*University of California, Berkeley*

*Thursday, April 28th*
*2:00 p.m. - 3:00 p.m.*
*In Person: John Crerar Library, Room 390*
*Remote: Live Stream <http://live.cs.uchicago.edu/stellayu/> or Zoom
<https://uchicago.zoom.us/j/91543229070?pwd=NkI5MmRzMGszbm5sSExJbVBvUTIzdz09>
(details
below)*


*Learning Mid-Level Vision from Natural Data*

Computer vision with deep learning has achieved super-human performance on
various benchmarks. However, deep neural network models are highly
specialized for the task and the data they are trained on. In contrast,
human vision is universal: It is a flexible light meter, an instant
geometer, a versatile material comparator, and a holistic parser. More
importantly, babies with normal vision eventually all learn to see out of
an initial nebulous blur and from their widely different visual experiences.

I attribute this fascinating development of universal visual perception to
the ability of learning mid-level visual representations from natural data
without any external supervision. My key insight is that there are
structures in the visual data that can be discovered with model bottlenecks
and minimal priors. I will present our stream of efforts on unsupervised
learning of visual recognition: seeing objectness (figure/ground) from
watching unlabeled videos, recognizing individual objects and parsing a
visual scene into hierarchical semantic concepts simply from a collection
of unlabeled images. Our data-driven computational modeling not only sheds
light on human visual perception, but also opens up exciting new ways for
scientists, engineers, and clinicians to look at their data and make novel
discoveries.

*Bio*: Stella Yu <https://www1.icsi.berkeley.edu/~stellayu/> received her
Ph.D. from Carnegie Mellon University, where she studied robotics at the
Robotics Institute and vision science at the Center for the Neural Basis of
Cognition. She is currently the Director of Vision Group at the
International Computer Science Institute, a Senior Fellow at the Berkeley
Institute for Data Science, and on the faculty of Computer Science, Vision
Science, Cognitive and Brain Sciences at UC Berkeley. Dr. Yu is interested
not only in understanding visual perception from multiple perspectives, but
also in using computer vision and machine learning to automate and exceed
human expertise in practical applications. Her group currently focuses on
complex-valued deep learning, sound-vision integration, and actionable
mid-level representation learning from non-curated data with minimal human
annotations. Dr. Yu leads multiple interdisciplinary projects and has a
strong track record of joint research and successful product deployment.

*Host*: Michael Maire

*Zoom Info:*
https://uchicago.zoom.us/j/91543229070?pwd=NkI5MmRzMGszbm5sSExJbVBvUTIzdz09
Meeting ID: 915 432 29070
Password: ds2022
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