The paper introduces TruncGradGS, a piecewise truncated gradient approach that mitigates gradient vanishing in 3D Gaussian Splatting, enhancing optimization stability and robustness to initializations. It demonstrates consistent improvements over random and COLMAP initializations in both static and dynamic settings. Additionally, the authors highlight limitations of existing dynamic scene benchmarks and present a new synthetic dataset for evaluating dynamic Gaussian Splatting.
By Theo Morales, Nhat-Quynh Le-Pham, Robin Atkins, Binh-Son Hua
F4Splat introduces a feed‑forward predictive densification strategy for 3D Gaussian splatting that allocates Gaussians based on a densification‑score guided by spatial complexity and multi‑view overlap. The method predicts per‑region scores to estimate required Gaussian density, enabling explicit control over the total Gaussian budget without retraining. This adaptive allocation reduces redundancy in simple regions and minimizes duplicate Gaussians across overlapping views, yielding compact yet high‑quality 3D representations and superior novel‑view synthesis performance with fewer Gaussians.
By Injae Kim, Chaehyeon Kim, Minseong Bae, Minseok Joo, Hyunwoo J. Kim
InceptionGS is a method that improves large‑scale Gaussian splatting for scenes captured with unstructured view sampling. It starts from an initial Gaussian splatting and selectively repairs areas affected by sparse views by integrating scene‑ and view‑adaptive generative priors, while keeping well‑covered regions unchanged. Experiments on real‑world scenes show that this hybrid reconstruction‑generation approach yields higher‑fidelity results than existing methods.
By Tianheng Lu, Guangyu Wang, Ruqi Huang, Lu Fang
InceptionGS is a method that improves large‑scale Gaussian splatting for scenes captured with unstructured view sampling. It starts from an initial Gaussian splatting and then selectively repairs regions that suffer from sparse views by incorporating adaptive generative priors, while preserving quality in well‑sampled areas. Experiments on real‑world scenes show that this balanced reconstruction‑generation approach yields higher‑fidelity results and works broadly across unstructured imagery.
arXiv:2609.36969v1 Announce Type: new
Abstract: 3D Gaussian Splatting (3DGS) is a state-of-the-art technique for 3D scene rendering, offering high efficiency and excellent visual quality. However, be...
By Gyeonggwan Lee, Seunghwan Hong, Junghun Suh
arXiv:2609.39553v1 Announce Type: new
Abstract: 3D Gaussian Splatting (3DGS) enables real-time novel view synthesis, but existing general-purpose acceleration methods suffer severe rendering quality...
By Changbai Li, Shuo Yang, Yichen Yang, Shuwei Shao, Huobin Tan