2 citations · 2 across the 9 of their papers we have counts for
11 papers
GS-Voxel: Fitting-Free Structured Latents for Large-Scale 3DGS Generation
Ming Qian, Zijian Wang, Minchao Sun +5
Many scalable latent 3D generators operate on structured tensors, whereas pre-optimized 3D Gaussian Splatting (3DGS) reconstructions are unordered, spatially irregular, and vary wi…
LagrangianSplats: Divergence-Free Transport of Gaussian Primitives for Fluid Reconstruction
Ningxiao Tao, Baoquan Chen, Mengyu Chu
Reconstructing 3D fluid velocity fields from sparse 2D video observations is a highly ill-posed inverse problem, demanding both transport consistency with observed motion and physi…
FieryGS: In-the-Wild Fire Synthesis with Physics-Integrated Gaussian Splatting
Qianfan Shen, Ningxiao Tao, Qiyu Dai +6
We consider the problem of synthesizing photorealistic, physically plausible combustion effects in in-the-wild 3D scenes. Traditional CFD and graphics pipelines can produce realist…
RefracGS: Novel View Synthesis Through Refractive Water Surfaces with 3D Gaussian Ray Tracing
Yiming Shao, Qiyu Dai, Chong Gao +6
Novel view synthesis (NVS) through non-planar refractive surfaces presents fundamental challenges due to severe, spatially varying optical distortions. While recent representations…
Robust Single-shot Structured Light 3D Imaging via Neural Feature Decoding
Jiaheng Li, Qiyu Dai, Lihan Li +4
We consider the problem of active 3D imaging using single-shot structured light systems, which are widely employed in commercial 3D sensing devices such as Apple Face ID and Intel…
From Orbit to Ground: Generative City Photogrammetry from Extreme Off-Nadir Satellite Images
Fei Yu, Yu Liu, Luyang Tang +10
City-scale 3D reconstruction from satellite imagery presents the challenge of extreme viewpoint extrapolation, where our goal is to synthesize ground-level novel views from sparse…
PointCNN++: Performant Convolution on Native Points
Lihan Li, Haofeng Zhong, Rui Bu +4
Existing convolutional learning methods for 3D point cloud data are divided into two paradigms: point-based methods that preserve geometric precision but often face performance cha…
The Less You Depend, The More You Learn: Synthesizing Novel Views from Sparse, Unposed Images with Minimal 3D Knowledge
Haoru Wang, Kai Ye, Minghan Qin +3
Recent advances in feed-forward Novel View Synthesis (NVS) have led to a divergence between two design philosophies: bias-driven methods, which rely on explicit 3D knowledge, such…
RainyGS: Efficient Rain Synthesis with Physically-Based Gaussian Splatting
Qiyu Dai, Xingyu Ni, Qianfan Shen +3
We consider the problem of adding dynamic rain effects to in-the-wild scenes in a physically-correct manner. Recent advances in scene modeling have made significant progress, with…
GeoSplatting: Towards Geometry Guided Gaussian Splatting for Physically-based Inverse Rendering
Kai Ye, Chong Gao, Guanbin Li +2
Recent 3D Gaussian Splatting (3DGS) representations have demonstrated remarkable performance in novel view synthesis; further, material-lighting disentanglement on 3DGS warrants re…
4D-Rotor Gaussian Splatting: Towards Efficient Novel View Synthesis for Dynamic Scenes
Yuanxing Duan, Fangyin Wei, Qiyu Dai +3
We consider the problem of novel-view synthesis (NVS) for dynamic scenes. Recent neural approaches have accomplished exceptional NVS results for static 3D scenes, but extensions to…