6 papers
Neural Constitutive Learning for Generalized Reaction-Diffusion Systems
Shang-Ke Chen, Yu-Peng Wang, Shih-Hsuan Hung +4
Generalized reaction-diffusion systems encompass diverse transport mechanisms and coupled reaction kinetics. A central question for neural PDE solvers is what should be learned so…
G3AR: Graph-Guided Neural Visual Geometry for Scalable Multi-Sequence Aerial Registration
Jeng Wen Joshua Lean, Ting-Yu Yen, Wei-Fang Sun +3
Full-context neural visual geometry is impractical for thousands of images, while sequence-based chunking poorly captures irregular non-local overlap in multi-sequence aerial colle…
Vis4GS: A Visual Analytic Tool for 3D Gaussian Splatting Reconstruction
Kai-Yuan Lin, Aryabima Mandala Putra, Jui-Chi Lee +1
3D Gaussian Splatting (3DGS) supports fast training and real-time rendering, but its optimization process remains difficult to interpret. Existing viewers mainly expose the final r…
ATG: Adaptive Anisotropic Textured Gaussians for Efficient 3D Scene Representation
Sheng-Chi Hsu, Ting-Yu Yen, Shih-Hsuan Hung +1
Gaussian Splatting has emerged as a powerful representation for high-quality, real-time 3D scene rendering. While recent works extend Gaussians with learnable textures to enrich vi…
PFGS: Pose-Fused 3D Gaussian Splatting for Complete Multi-Pose Object Reconstruction
Ting-Yu Yen, Yu-Sheng Chiu, Shih-Hsuan Hung +2
Recent advances in 3D Gaussian Splatting (3DGS) have enabled high-quality, real-time novel-view synthesis from multi-view images. However, most existing methods assume the object i…
LoBE-GS: Load-Balanced and Efficient 3D Gaussian Splatting for Large-Scale Scene Reconstruction
Sheng-Hsiang Hung, Ting-Yu Yen, Wei-Fang Sun +3
3D Gaussian Splatting (3DGS) has established itself as an efficient representation for real-time, high-fidelity 3D scene reconstruction. However, scaling 3DGS to large and unbounde…