3D Gaussian
3D Gaussian splatting is an explicit 3D scene representation technique that uses collections of 3D Gaussian functions to model objects and scenes, aiming for high-quality, real-time rendering. Current research focuses on improving the accuracy and efficiency of 3D Gaussian splatting, particularly addressing challenges like view-dependent effects, sparse viewpoints, and the handling of dynamic objects and large-scale scenes through various optimization strategies and model architectures. This approach offers significant advantages in applications such as novel view synthesis, 3D object detection, augmented reality, and even multimodal place recognition by providing a compact yet detailed representation of 3D environments.
Papers
FlashSplat: 2D to 3D Gaussian Splatting Segmentation Solved Optimally
Qiuhong Shen, Xingyi Yang, Xinchao Wang
Thermal3D-GS: Physics-induced 3D Gaussians for Thermal Infrared Novel-view Synthesis
Qian Chen, Shihao Shu, Xiangzhi Bai
SwinGS: Sliding Window Gaussian Splatting for Volumetric Video Streaming with Arbitrary Length
Bangya Liu, Suman Banerjee
GigaGS: Scaling up Planar-Based 3D Gaussians for Large Scene Surface Reconstruction
Junyi Chen, Weicai Ye, Yifan Wang, Danpeng Chen, Di Huang, Wanli Ouyang, Guofeng Zhang, Yu Qiao, Tong He
MVGaussian: High-Fidelity text-to-3D Content Generation with Multi-View Guidance and Surface Densification
Phu Pham, Aradhya N. Mathur, Ojaswa Sharma, Aniket Bera