Presentation
Anchored 4D Gaussian Splatting for Dynamic Novel View Synthesis
DescriptionNovel view synthesis for dynamic scenes is a challenging problem in computer graphics. While recent 3D Gaussian splatting methods have achieved state-of-the-art quality and speed for static scenes, their extension to 4D dynamic scenes remains non-trivial. Existing methods for dynamic scene novel view synthesis either employ time-varying dynamic Gaussians, which often produce artifacts due to MLP limitations, or directly extend Gaussians to 4D, yielding high rendering quality but incurring substantial memory overhead. This paper introduces a novel 4D anchor-based framework that leverages the stronger representational power of 4D Gaussians while addressing their memory inefficiency. Our approach effectively models dynamic scenes by binding Gaussians to anchor points and strategically distributing these anchor locations. Furthermore, we propose a novel dynamic anchor growing strategy to generate additional anchors in dynamic regions requiring reconstruction. Additionally, we design an anchor stabilization strategy to fix the attributes of anchors in static regions during training, thereby preventing anchor redundancy. Extensive experiments across various benchmarks, including N3DV and the Technicolor dataset, demonstrate our method's excellent visual quality.
Event Type
Technical Papers
TimeTuesday, 16 December 20253:11pm - 3:22pm HKT
LocationMeeting Room S421, Level 4