3 papers
cs.CV2025
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…
cs.CV2025
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…
cs.CV2025
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,…