{
  "title": "LPIPS",
  "kind": "entities",
  "body_text": "# LPIPS\n\n## Incoming relations\n\n- **uses_metric** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_\n- **uses_metric** → AGG: Amortized Generative 3D Gaussians for Single Image to 3D _(Paper)_\n- **uses_metric** → About nerfstudio-project/gsplat _(Repository)_\n- **uses_metric** → BARF: Bundle-Adjusting Neural Radiance Fields _(Paper)_\n- **uses_metric** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM _(Paper)_\n- **uses_metric** → DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras _(Paper)_\n- **uses_metric** → DeepV2D: Video to Depth with Differentiable Structure from Motion _(Paper)_\n- **uses_metric** → Direct Sparse Odometry _(Paper)_\n- **uses_metric** → DreamFusion: Text-to-3D using 2D Diffusion _(Paper)_\n- **uses_metric** → DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation _(Paper)_\n- **uses_metric** → Dynamic View Synthesis from Dynamic Monocular Video _(Paper)_\n- **uses_metric** → Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields _(Paper)_\n- **uses_metric** → GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting _(Paper)_\n- **uses_metric** → GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting _(Paper)_\n- **uses_metric** → Gaussian Splatting SLAM _(Paper)_\n- **uses_metric** → HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields _(Paper)_\n- **uses_metric** → Implicit Geometric Regularization for Learning Shapes _(Paper)_\n- **uses_metric** → Instant Neural Graphics Primitives with a Multiresolution Hash Encoding _(Paper)_\n- **uses_metric** → Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model _(Paper)_\n- **uses_metric** → K-Planes: Explicit Radiance Fields in Space, Time, and Appearance _(Paper)_\n- **uses_metric** → LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation _(Paper)_\n- **uses_metric** → LRM: Large Reconstruction Model for Single Image to 3D _(Paper)_\n- **uses_metric** → LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes _(Paper)_\n- **uses_metric** → MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes _(Paper)_\n- **uses_metric** → Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors _(Paper)_\n\n## Connected node types\n\n- Paper: 45\n- Repository: 1",
  "source_path": "/home/runner/work/Tesserae/Tesserae/examples/demo-corpus/data/research/papers/arxiv-1607-02565/abstract.md",
  "links": [],
  "body": "# LPIPS\n\n## Incoming relations\n\n- **uses_metric** → 2D Gaussian Splatting for Geometrically Accurate Radiance Fields _(Paper)_\n- **uses_metric** → AGG: Amortized Generative 3D Gaussians for Single Image to 3D _(Paper)_\n- **uses_metric** → About nerfstudio-project/gsplat _(Repository)_\n- **uses_metric** → BARF: Bundle-Adjusting Neural Radiance Fields _(Paper)_\n- **uses_metric** → Co-SLAM: Joint Coordinate and Sparse Parametric Encodings for Neural Real-Time SLAM _(Paper)_\n- **uses_metric** → DROID-SLAM: Deep Visual SLAM for Monocular, Stereo, and RGB-D Cameras _(Paper)_\n- **uses_metric** → DeepV2D: Video to Depth with Differentiable Structure from Motion _(Paper)_\n- **uses_metric** → Direct Sparse Odometry _(Paper)_\n- **uses_metric** → DreamFusion: Text-to-3D using 2D Diffusion _(Paper)_\n- **uses_metric** → DreamGaussian: Generative Gaussian Splatting for Efficient 3D Content Creation _(Paper)_\n- **uses_metric** → Dynamic View Synthesis from Dynamic Monocular Video _(Paper)_\n- **uses_metric** → Feature 3DGS: Supercharging 3D Gaussian Splatting to Enable Distilled Feature Fields _(Paper)_\n- **uses_metric** → GALA3D: Towards Text-to-3D Complex Scene Generation via Layout-guided Generative Gaussian Splatting _(Paper)_\n- **uses_metric** → GS-SLAM: Dense Visual SLAM with 3D Gaussian Splatting _(Paper)_\n- **uses_metric** → Gaussian Splatting SLAM _(Paper)_\n- **uses_metric** → HyperNeRF: A Higher-Dimensional Representation for Topologically Varying Neural Radiance Fields _(Paper)_\n- **uses_metric** → Implicit Geometric Regularization for Learning Shapes _(Paper)_\n- **uses_metric** → Instant Neural Graphics Primitives with a Multiresolution Hash Encoding _(Paper)_\n- **uses_metric** → Instant3D: Fast Text-to-3D with Sparse-View Generation and Large Reconstruction Model _(Paper)_\n- **uses_metric** → K-Planes: Explicit Radiance Fields in Space, Time, and Appearance _(Paper)_\n- **uses_metric** → LGM: Large Multi-View Gaussian Model for High-Resolution 3D Content Creation _(Paper)_\n- **uses_metric** → LRM: Large Reconstruction Model for Single Image to 3D _(Paper)_\n- **uses_metric** → LucidDreamer: Domain-free Generation of 3D Gaussian Splatting Scenes _(Paper)_\n- **uses_metric** → MERF: Memory-Efficient Radiance Fields for Real-time View Synthesis in Unbounded Scenes _(Paper)_\n- **uses_metric** → Magic123: One Image to High-Quality 3D Object Generation Using Both 2D and 3D Diffusion Priors _(Paper)_\n\n## Connected node types\n\n- Paper: 45\n- Repository: 1",
  "frontmatter": {
    "kind": "entities",
    "node_id": "Metric:lpips:e4a3fb2e13e5",
    "node_type": "Metric",
    "source_path": "/home/runner/work/Tesserae/Tesserae/examples/demo-corpus/data/research/papers/arxiv-1607-02565/abstract.md",
    "title": "LPIPS"
  }
}