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VERSION:2.0
PRODID:IEEE vTools.Events//EN
CALSCALE:GREGORIAN
BEGIN:VTIMEZONE
TZID:Asia/Shanghai
BEGIN:STANDARD
DTSTART:19910915T010000
TZOFFSETFROM:+0900
TZOFFSETTO:+0800
TZNAME:CST
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BEGIN:VEVENT
DTSTAMP:20231118T083345Z
UID:10A131E3-A5EE-4FED-88EC-F14770C1F54F
DTSTART;TZID=Asia/Shanghai:20221129T160000
DTEND;TZID=Asia/Shanghai:20221129T180000
DESCRIPTION:In this lecture\, Professor Luigi Di Stefano will introduce his
  research journey in the field of computer vision research. He has been re
 searching on computer vision since more than 30 years. In the talk he will
  discuss how computer vision has evolved from a programmed to a fully data
 -driven computational paradigm\, thanks to the advent of machine learning 
 and then deep learning. He will also highlight how this transformation has
  broadened the spectrum of computer vision applications\, inasmuch as nowa
 days we witness researchers addressing new generative tasks that were just
  unthinkable only a few years (if not months\, sometimes !) ago. In his ta
 lk he will also focus on how deep learning has been successful in yielding
  state-of-the-art performance also in tasks\, like\, e.g.\, depth estimati
 on\, where one cannot rely on ground-truth data to supervise the learning 
 process. Professor Luigi Di Stefano will present some recent research resu
 lts achieved by his Lab and published in CVPR 2019\, CVPR 2020 and CVPR 20
 22\, he well as in 3DV 2021 (Best Paper Award Honorable Mention) and 3DV 2
 022.\n\nVirtual: https://events.vtools.ieee.org/m/384689
LOCATION:Virtual: https://events.vtools.ieee.org/m/384689
ORGANIZER:ting_lu@hnu.edu.cn
SEQUENCE:23
SUMMARY:A journey through computer vision
URL;VALUE=URI:https://events.vtools.ieee.org/m/384689
X-ALT-DESC:Description: <br /><p>In this lecture\, Professor Luigi Di Stefa
 no will introduce his research journey in the field of computer vision res
 earch. He&nbsp\;has&nbsp\;been researching on computer vision since more t
 han 30 years. In the talk he will discuss how computer vision has evolved 
 from a programmed to a fully data-driven computational paradigm\, thanks t
 o the advent of machine learning and then deep learning. He will also high
 light how this transformation has broadened the spectrum of computer visio
 n applications\, inasmuch as nowadays we witness researchers addressing ne
 w generative tasks that were just unthinkable only a few years (if not mon
 ths\, sometimes !) ago. In his talk he will also focus on how deep learnin
 g has been successful in yielding state-of-the-art performance also in tas
 ks\, like\, e.g.\, depth estimation\, where one cannot rely on ground-trut
 h data to supervise the learning process. Professor Luigi Di Stefano will 
 present some recent research results achieved by his Lab and published in 
 CVPR 2019\, CVPR 2020 and CVPR 2022\, he well as in 3DV 2021 (Best Paper A
 ward Honorable Mention) and 3DV 2022.</p>
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