BEGIN:VCALENDAR
VERSION:2.0
PRODID:Linklings LLC
BEGIN:VTIMEZONE
TZID:Australia/Melbourne
X-LIC-LOCATION:Australia/Melbourne
BEGIN:DAYLIGHT
TZOFFSETFROM:+1000
TZOFFSETTO:+1100
TZNAME:AEDT
DTSTART:19721003T020000
RRULE:FREQ=YEARLY;BYMONTH=4;BYDAY=1SU
END:DAYLIGHT
BEGIN:STANDARD
DTSTART:19721003T020000
TZOFFSETFROM:+1100
TZOFFSETTO:+1000
TZNAME:AEST
RRULE:FREQ=YEARLY;BYMONTH=10;BYDAY=1SU
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTAMP:20260114T163644Z
LOCATION:Meeting Room C4.8\, Level 4 (Convention Centre)
DTSTART;TZID=Australia/Melbourne:20231213T153500
DTEND;TZID=Australia/Melbourne:20231213T154500
UID:siggraphasia_SIGGRAPH Asia 2023_sess145_papers_837@linklings.com
SUMMARY:SeamlessNeRF: Stitching Part NeRFs with Gradient Propagation
DESCRIPTION:Bingchen Gong and Yuehao Wang (The Chinese University of Hong 
 Kong); Xiaoguang Han (Shenzhen Research Institute of Big Data, the Chinese
  University of Hong Kong (Shenzhen)); and Qi Dou (The Chinese University o
 f Hong Kong)\n\nNeural Radiance Fields (NeRFs) have emerged as a promising
  representation for 3D scenes, sparking a surge in research aimed at exten
 ding the editing capabilities in this domain. The task of seamless editing
  and merging of different NeRFs, similar to the "copy-and-paste" function 
 in 2D image editing, remains a critical operation that current methods str
 uggle to accomplish. To address these challenges, we propose SeamlessNeRF,
  a novel approach for seamless merging and editing of multiple NeRFs. Our 
 method optimizes radiance fields within a merged NeRF representation and f
 ocuses on the boundary area where different radiance fields intersect, ali
 gning radiance color and preserving the gradient field of the target. This
  technique allows for a seamless and natural fusion of NeRFs, while overco
 ming limitations faced by traditional image-based melding methods. To the 
 best of our knowledge, SeamlessNeRF is the first to offer such capabilitie
 s, advancing the field of 3D editing with an innovative gradient propagati
 on method for radiance fields. Our method provides a robust solution for c
 omplex scene composition and intricate character modeling, validated by ex
 tensive experimental results. Through SeamlessNeRF, we make the first step
  towards a seamless, efficient, and intuitive approach to editing in the r
 ealm of 3D representations.\n\nRegistration Category: Full Access\n\nSessi
 on Chair: Young J. Kim (Ewha Womans University)\n\n
URL:https://asia.siggraph.org/2023/full-program?id=papers_837&sess=sess145
END:VEVENT
END:VCALENDAR