arXiv Machine Learning

Complex-Valued 2D Gaussian Representation for Computer-Generated Holography

arXiv:2511. 15022v2 Announce Type: replace-cross Abstract: Complex-valued Gaussian primitives have recently been explored for representing holographic radiance fields in 3D novel view synthesis.

arXiv AI
Jun 3

Ref-DGS: Reflective Dual Gaussian Splatting

arXiv:2603. 07664v3 Announce Type: replace-cross Abstract: The reflective appearance, especially strong and typically near-field specular reflections, poses a fundamental challenge for accurate surface reconstruction and novel view synthesis.

By Ningjing Fan, Yiqun Wang, Dongming Yan, Peter Wonka
arXiv Machine Learning
Jun 30

Efficient 3D Gaussian Splatting with Axis-Shared Rasterization and Order-independent Transmittance

arXiv:2506. 07069v2 Announce Type: replace-cross Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful technique for novel view synthesis, combining high-quality reconstruction with efficient rendering.

By Zhican Wang, Guanghui He, Lingjun Gao, Dantong Liu, Shell Xu Hu, Chen Zhang, Zhuoran Song, Nicholas Lane, Hongxiang Fan
Hugging Face Trending Papers
Aug 3

FAST-GS: Frequency Aware Space-time Gaussian Splatting for Photorealistic Dynamic Novel View Synthesis

4D Gaussian Splatting (4DGS) excels in dynamic 3D reconstruction and real-time novel view synthesis via efficient 4D Gaussian representations and parallelizable rendering. However, existing 4DGS approaches rely on a single polynomial to model motion, which limits performance in complex dynamic scenes where high-frequency motion components are prevalent, and fails to ensure long-term stability due to cumulative trajectory drift.