#Gaussian Splatting

LangSplat employs Gaussian splatting for 3D language model generation, integrating language features into SfM datasets. The project includes a PyTorch-based optimizer and scene-wise autoencoding, offers pre-trained models, and datasets like 3D-OVS and LERF, facilitating 3D scene processing innovations. It supports 3D object localization and semantic segmentation.

Discover the StyleGaussian project, a unique 3D style transfer system offering real-time transformations with full multi-view consistency. The PyTorch implementation uses Gaussian Splatting for effective style changes. Style transfers can be conducted through an interactive remote viewer or inference rendering with multiple styles. Detailed installation, quick start instructions, and training options—either from scratch or with pretrained models—ensure versatility in 3D artistic visualizations.

The project employs Gaussian splatting for structured 3D talking head synthesis, delivering realistic animations without compromising model integrity. Comprehensive setup instructions cover necessary environments like PyTorch and TensorFlow, alongside crucial model preparation steps including face parsing and 3DMM application for head pose tracking. Ethical usage is emphasized throughout, with datasets sourced in compliance with copyright standards. This resource is well-suited for researchers exploring cutting-edge 3D synthesis strategies.

This UE5 plugin by XVERSE Technology implements Gaussian Splatting for real-time 3D scene reconstruction, providing capabilities for visualization, management, and scalable rendering. Features include Niagara integration for efficient rendering, easy import of .ply files, and hybrid rendering with existing UE assets. It supports over 200,000 point clouds with automatic LOD and dynamic illumination. Future updates will enhance LOD rendering, collision detection, and allow interactive editing, offering a complete solution for 3D asset management in Unreal Engine 5.