94 citations · 109 across the 5 of their papers we have counts for
5 papers
LLGS: Unsupervised Gaussian Splatting for Image Enhancement and Reconstruction in Pure Dark Environment
Haoran Wang, Jingwei Huang, Lu Yang +3
3D Gaussian Splatting has shown remarkable capabilities in novel view rendering tasks and exhibits significant potential for multi-view optimization.However, the original 3D Gaussi…
DenseSplat: Densifying Gaussian Splatting SLAM with Neural Radiance Prior
Mingrui Li, Shuhong Liu, Tianchen Deng +1
Gaussian SLAM systems excel in real-time rendering and fine-grained reconstruction compared to NeRF-based systems. However, their reliance on extensive keyframes is impractical for…
Technique Report of CVPR 2024 PBDL Challenges
Ying Fu, Yu Li, Shaodi You +96
The intersection of physics-based vision and deep learning presents an exciting frontier for advancing computer vision technologies. By leveraging the principles of physics to info…
SGS-SLAM: Semantic Gaussian Splatting For Neural Dense SLAM
Mingrui Li, Shuhong Liu, Heng Zhou +4
We present SGS-SLAM, the first semantic visual SLAM system based on Gaussian Splatting. It incorporates appearance, geometry, and semantic features through multi-channel optimizati…
DDN-SLAM: Real-time Dense Dynamic Neural Implicit SLAM
Mingrui Li, Yiming Zhou, Guangan Jiang +3
SLAM systems based on NeRF have demonstrated superior performance in rendering quality and scene reconstruction for static environments compared to traditional dense SLAM. However,…