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X-WR-CALNAME:Visual Recognition beyond Appearances\, and its Robotic Applic
ations
X-WR-TIMEZONE:America/Los_Angeles
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UID:2021-01-25-yezhou-yang@cml.ics.uci.edu
DTSTAMP:20210125T000000Z
SEQUENCE:57690
DTSTART;TZID=America/Los_Angeles:20210125T130000
DTEND;TZID=America/Los_Angeles:20210125T140000
SUMMARY:[CML Seminar] Yezhou Yang: Visual Recognition beyond Appearances\,
and its Robotic Applications
LOCATION:Online (live stream)
DESCRIPTION:Yezhou Yang\, Assistant Professor\, School of Computing\, Infor
matics\, and Decision Systems Engineering\, Arizona State University\n\nTi
tle: Visual Recognition beyond Appearances\, and its Robotic Applications\
n\nAbstract: The goal of Computer Vision is to develop algorithms to answe
r What is Where at When from visual appearance. The speaker recognizes the
importance of studying underlying entities and relations beyond visual ap
pearance\, following an Active Perception paradigm. This talk presents eff
orts ranging from reasoning beyond appearance for visual question answerin
g\, image understanding\, and video captioning\, through temporal knowledg
e distillation with incremental knowledge transfer\, to their roles in a r
obotic visual learning framework via a robotic indoor object search task.
The talk also features the Active Perception Group's ongoing projects in a
utonomous driving\, AI security\, and healthcare.\n\nhttps://cml.ics.uci.e
du/seminars/2021-01-25-yezhou-yang
X-ALT-DESC;FMTTYPE=text/html:Yezhou Yang\, Assistant Pro
fessor\, School of Computing\, Informatics\, and Decision Systems Engineer
ing\, Arizona State University
Title: Visual Recognition bey
ond Appearances\, and its Robotic Applications
Abstract: The
goal of Computer Vision is to develop algorithms to answer What is Where
at When from visual appearance. The speaker recognizes the importance of s
tudying underlying entities and relations beyond visual appearance\, follo
wing an Active Perception paradigm. This talk presents efforts ranging fro
m reasoning beyond appearance for visual question answering\, image unders
tanding\, and video captioning\, through temporal knowledge distillation w
ith incremental knowledge transfer\, to their roles in a robotic visual le
arning framework via a robotic indoor object search task. The talk also fe
atures the Active Perception Group's ongoing projects in autonomous drivin
g\, AI security\, and healthcare.
https://cml.ics.uci.edu/seminars/2021-01-
25-yezhou-yang
URL:https://cml.ics.uci.edu/seminars/2021-01-25-yezhou-yang
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