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VERSION:2.0
PRODID:Linklings LLC
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TZID:Asia/Hong_Kong
X-LIC-LOCATION:Asia/Hong_Kong
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TZOFFSETFROM:+0800
TZOFFSETTO:+0800
TZNAME:HKT
DTSTART:19911015T033000
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BEGIN:VEVENT
DTSTAMP:20251218T030656Z
LOCATION:Meeting Room S421\, Level 4
DTSTART;TZID=Asia/Hong_Kong:20251216T151100
DTEND;TZID=Asia/Hong_Kong:20251216T152200
UID:siggraphasia_SIGGRAPH Asia 2025_sess124_papers_1616@linklings.com
SUMMARY:Anchored 4D Gaussian Splatting for Dynamic Novel View Synthesis
DESCRIPTION:Yilong Li, Bo Pang, Yisong Chen, and Guoping Wang (Peking Univ
 ersity)\n\nNovel view synthesis for dynamic scenes is a challenging proble
 m in computer graphics. While recent 3D Gaussian splatting methods have ac
 hieved state-of-the-art quality and speed for static scenes, their extensi
 on to 4D dynamic scenes remains non-trivial. Existing methods for dynamic 
 scene novel view synthesis either employ time-varying dynamic Gaussians, w
 hich often produce artifacts due to MLP limitations, or directly extend Ga
 ussians to 4D, yielding high rendering quality but incurring substantial m
 emory overhead. This paper introduces a novel 4D anchor-based framework th
 at leverages the stronger representational power of 4D Gaussians while add
 ressing their memory inefficiency. Our approach effectively models dynamic
  scenes by binding Gaussians to anchor points and strategically distributi
 ng these anchor locations. Furthermore, we propose a novel dynamic anchor 
 growing strategy to generate additional anchors in dynamic regions requiri
 ng reconstruction. Additionally, we design an anchor stabilization strateg
 y to fix the attributes of anchors in static regions during training, ther
 eby preventing anchor redundancy. Extensive experiments across various ben
 chmarks, including N3DV and the Technicolor dataset, demonstrate our metho
 d's excellent visual quality.\n\nRegistration Category: Full Access, Full 
 Access Supporter\n\nSession Chair: Yan-Pei Cao (VAST)\n\n
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