5 papers
AsySplat: Efficient Asymmetric 3D Gaussian Splatting for Long-Sequence Scene Modeling
Yingji Zhong, Dave Zhenyu Chen, Fuzhao Ou +4
Recent generalizable 3D Gaussian Splatting models have advanced long-sequence novel view synthesis (NVS), but at the cost of substantial redundant computation. We identify that the…
Quantifying and Alleviating Co-Adaptation in Sparse-View 3D Gaussian Splatting
Kangjie Chen, Yingji Zhong, Zhihao Li +4
3D Gaussian Splatting (3DGS) has demonstrated impressive performance in novel view synthesis under dense-view settings. However, in sparse-view scenarios, despite the realistic ren…
Taming Video Diffusion Prior with Scene-Grounding Guidance for 3D Gaussian Splatting from Sparse Inputs
Yingji Zhong, Zhihao Li, Dave Zhenyu Chen +2
Despite recent successes in novel view synthesis using 3D Gaussian Splatting (3DGS), modeling scenes with sparse inputs remains a challenge. In this work, we address two critical y…
Empowering Sparse-Input Neural Radiance Fields with Dual-Level Semantic Guidance from Dense Novel Views
Yingji Zhong, Kaichen Zhou, Zhihao Li +3
Neural Radiance Fields (NeRF) have shown remarkable capabilities for photorealistic novel view synthesis. One major deficiency of NeRF is that dense inputs are typically required,…
MagicDrive3D: Controllable 3D Generation for Any-View Rendering in Street Scenes
Ruiyuan Gao, Kai Chen, Zhihao Li +3
Controllable generative models for images and videos have seen significant success, yet 3D scene generation, especially in unbounded scenarios like autonomous driving, remains unde…