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Curated list of papers and resources focused on 3D Gaussian Splatting, intended to keep pace with the anticipated surge of research in the coming months.
A PyTorch Library for Accelerating 3D Deep Learning Research
3D Gaussian Splat Editor
FAST-LIVO2: Fast, Direct LiDAR-Inertial-Visual Odometry
[CVPR 2024] 4D Gaussian Splatting for Real-Time Dynamic Scene Rendering
[CVPR 2024] Official PyTorch implementation of SuGaR: Surface-Aligned Gaussian Splatting for Efficient 3D Mesh Reconstruction and High-Quality Mesh Rendering
pySLAM is a hybrid Python/C++ Visual SLAM pipeline supporting monocular, stereo, and RGB-D cameras. It provides a broad set of modern local and global feature extractors, multiple loop-closure strategies, a volumetric reconstruction module, integrated depth-prediction models, and semantic segmentation capabilities for enhanced scene understanding.
[SIGGRAPH'24] 2D Gaussian Splatting for Geometrically Accurate Radiance Fields
Train, inspect, edit, automate, and export 3D Gaussian Splatting scenes from a single native application.
3D高斯论文，持续更新，欢迎交流讨论。
Three.js-based implementation of 3D Gaussian splatting
Ray tracing and hybrid rasterization of Gaussian particles
SplaTAM: Splat, Track & Map 3D Gaussians for Dense RGB-D SLAM (CVPR 2024)
[ECCV 2024 Oral] LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation.
[CVPR'24 Highlight & Best Demo Award] Gaussian Splatting SLAM
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