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cs.GR2026
Generative 3D Gaussians with Learned Density Control
Runjie Yan, Yan-Pei Cao, Peng Wang +2
We present Density-Sampled Gaussians (DeG), a novel 3D representation designed to bridge the gap between adaptive rendering primitives and scalable generative modeling. Unlike exis…
cs.CV2026
Softmax-GS: Generalized Gaussians Learning When to Blend or Bound
Chen Ziwen, Peng Wang, Hao Tan +2
3D Gaussian Splatting (3D GS) is widely adopted for novel view synthesis due to its high training and rendering efficiency. However, its efficiency relies on the key assumption tha…