3 papers
cs.CV2026
L2D2-GS: Learning to Densify for Feedforward Dynamic Gaussian Scene Reconstruction
Zetian Song, Chenming Wu, Junnan Liu +6
High-fidelity reconstruction of dynamic urban environments is a cornerstone of autonomous driving simulation and large-scale world modeling. While 3D Gaussian Splatting (3DGS) has…
cs.CV2025
TinySplat: Feedforward Approach for Generating Compact 3D Scene Representation
Zetian Song, Jiaye Fu, Jiaqi Zhang +4
The recent development of feedforward 3D Gaussian Splatting (3DGS) presents a new paradigm to reconstruct 3D scenes. Using neural networks trained on large-scale multi-view dataset…
cs.CV2025
ProSplat: Improved Feed-Forward 3D Gaussian Splatting for Wide-Baseline Sparse Views
Xiaohan Lu, Jiaye Fu, Jiaqi Zhang +3
Feed-forward 3D Gaussian Splatting (3DGS) has recently demonstrated promising results for novel view synthesis (NVS) from sparse input views, particularly under narrow-baseline con…