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X-WR-CALNAME:Radiance Fields Advancing 3D Scene Understanding for Robotics
and Autonomous Driving
X-WR-TIMEZONE:America/Los_Angeles
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UID:2025-04-28-matu-s-dopiriak@cml.ics.uci.edu
DTSTAMP:20250428T000000Z
SEQUENCE:57690
DTSTART;TZID=America/Los_Angeles:20250428T130000
DTEND;TZID=America/Los_Angeles:20250428T140000
SUMMARY:[CML Seminar] Matúš Dopiriak: Radiance Fields Advancing 3D Scene
Understanding for Robotics and Autonomous Driving
LOCATION:Donald Bren Hall 4011
DESCRIPTION:Matúš Dopiriak\, PhD Student\, Department of Computers and In
formatics\, Technical University in Košice\n\nTitle: Radiance Fields Adva
ncing 3D Scene Understanding for Robotics and Autonomous Driving\n\nAbstra
ct: Since emerging in 2020\, neural radiance fields (NeRFs) have marked a
transformative breakthrough in representing photorealistic 3D scenes. In t
he years that followed\, numerous variants have evolved\, enhancing perfor
mance\, enabling the capture of dynamic changes over time\, and tackling c
hallenges in large-scale environments. Among these\, NVIDIA's Instant-NGP
stood out\, earning recognition as one of TIME Magazine's Best Inventions
of 2022. Radiance fields now facilitate advanced 3D scene understanding\,
leveraging large language models (LLMs) and diffusion models to enable sop
histicated scene editing and manipulation. Their applications span robotic
s\, where they support planning\, navigation\, and manipulation. In autono
mous driving\, they serve as immersive simulation systems or can be used a
s digital twins for video compression integrated in edge computing archite
ctures. This lecture explores the evolution\, capabilities\, and practical
impact of radiance fields in these cutting-edge domains.\n\nhttps://cml.i
cs.uci.edu/seminars/2025-04-28-matu-s-dopiriak
X-ALT-DESC;FMTTYPE=text/html:Matúš Dopiriak\, PhD Stud
ent\, Department of Computers and Informatics\, Technical University in Ko
šice
Title: Radiance Fields Advancing 3D Scene Understandin
g for Robotics and Autonomous Driving
Abstract: Since emergi
ng in 2020\, neural radiance fields (NeRFs) have marked a transformative b
reakthrough in representing photorealistic 3D scenes. In the years that fo
llowed\, numerous variants have evolved\, enhancing performance\, enabling
the capture of dynamic changes over time\, and tackling challenges in lar
ge-scale environments. Among these\, NVIDIA's Instant-NGP stood out\, earn
ing recognition as one of TIME Magazine's Best Inventions of 2022. Radianc
e fields now facilitate advanced 3D scene understanding\, leveraging large
language models (LLMs) and diffusion models to enable sophisticated scene
editing and manipulation. Their applications span robotics\, where they s
upport planning\, navigation\, and manipulation. In autonomous driving\, t
hey serve as immersive simulation systems or can be used as digital twins
for video compression integrated in edge computing architectures. This lec
ture explores the evolution\, capabilities\, and practical impact of radia
nce fields in these cutting-edge domains.
https://cml.ics.uci.edu/semin
ars/2025-04-28-matu-s-dopiriak
URL:https://cml.ics.uci.edu/seminars/2025-04-28-matu-s-dopiriak
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