2 citations · 5 across the 12 of their papers we have counts for
9 papers · 1 filter
GS-RoadPatching: Inpainting Gaussians via 3D Searching and Placing for Driving Scenes
Guo Chen, Jiarun Liu, Sicong Du +5
This paper presents GS-RoadPatching, an inpainting method for driving scene completion by referring to completely reconstructed regions, which are represented by 3D Gaussian Splatt…
CMD: Constraining Multimodal Distribution for Domain Adaptation in Stereo Matching
Zhelun Shen, Zhuo Li, Chenming Wu +4
Recently, learning-based stereo matching methods have achieved great improvement in public benchmarks, where soft argmin and smooth L1 loss play a core contribution to their succes…
Splatter-360: Generalizable 360 Gaussian Splatting for Wide-baseline Panoramic Images
Zheng Chen, Chenming Wu, Zhelun Shen +5
Wide-baseline panoramic images are frequently used in applications like VR and simulations to minimize capturing labor costs and storage needs. However, synthesizing novel views fr…
DGTR: Distributed Gaussian Turbo-Reconstruction for Sparse-View Vast Scenes
Hao Li, Yuanyuan Gao, Haosong Peng +7
Novel-view synthesis (NVS) approaches play a critical role in vast scene reconstruction. However, these methods rely heavily on dense image inputs and prolonged training times, mak…
VDG: Vision-Only Dynamic Gaussian for Driving Simulation
Hao Li, Jingfeng Li, Dingwen Zhang +7
Dynamic Gaussian splatting has led to impressive scene reconstruction and image synthesis advances in novel views. Existing methods, however, heavily rely on pre-computed poses and…
HO-Gaussian: Hybrid Optimization of 3D Gaussian Splatting for Urban Scenes
Zhuopeng Li, Yilin Zhang, Chenming Wu +2
The rapid growth of 3D Gaussian Splatting (3DGS) has revolutionized neural rendering, enabling real-time production of high-quality renderings. However, the previous 3DGS-based met…