3D Gaussian Representation
3D Gaussian representation is an emerging technique for modeling and rendering 3D scenes, aiming to improve efficiency and quality compared to traditional methods. Current research focuses on developing and refining algorithms based on Gaussian splatting, often incorporating techniques like octrees for efficient storage and handling of large datasets, and integrating them with other models such as diffusion models for enhanced generation and manipulation capabilities. This approach shows promise for applications ranging from medical imaging (e.g., coronary artery reconstruction) to computer graphics (e.g., novel view synthesis and animation), offering faster rendering speeds and improved reconstruction quality in various domains. The compact nature of these representations also addresses the significant storage challenges associated with high-fidelity 3D models.
Papers
A Hierarchical 3D Gaussian Representation for Real-Time Rendering of Very Large Datasets
Bernhard Kerbl, Andréas Meuleman, Georgios Kopanas, Michael Wimmer, Alexandre Lanvin, George Drettakis
Effective Rank Analysis and Regularization for Enhanced 3D Gaussian Splatting
Junha Hyung, Susung Hong, Sungwon Hwang, Jaeseong Lee, Jaegul Choo, Jin-Hwa Kim