Diagnoses PVFD optimization drift in sparse-view Gaussian tomography and introduces LADES controller using annealed dropout and population-based stopping to enhance volumetric fidelity.
R 2- gaussian: Rectifying radiative gaussian splatting for tomographic reconstruction.arXiv preprint arXiv:2405.20693, 2024
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UNVERDICTED 4representative citing papers
3D Skew Gaussian Splatting extends standard 3D Gaussian Splatting with skew primitives, enhanced opacity, depth-aware densification, and a re-derived CUDA pipeline for a free-camera visualization engine.
DenZa-Gaussian adapts 3D Gaussian Splatting for ADF-STEM tomography by modeling scattering as a learnable scalar field, adding tilt-angle normalization, and using a Fourier amplitude loss to improve sparse-view 3D reconstructions.
3DGR-CT adapts 3D Gaussian splatting with FBP-guided initialization and differentiable CT projection for sparse-view reconstruction, claiming better accuracy and speed than prior methods.
citing papers explorer
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Projection-Volume Fidelity Divergence: Diagnosing and Controlling Optimization Drift in Sparse-View 3D Gaussian Tomography
Diagnoses PVFD optimization drift in sparse-view Gaussian tomography and introduces LADES controller using annealed dropout and population-based stopping to enhance volumetric fidelity.
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3D Skew Gaussian Splatting with Any Camera Trajectory Visualization Engine
3D Skew Gaussian Splatting extends standard 3D Gaussian Splatting with skew primitives, enhanced opacity, depth-aware densification, and a re-derived CUDA pipeline for a free-camera visualization engine.
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3D Gaussian Splatting for Annular Dark Field Scanning Transmission Electron Microscopy Tomography Reconstruction
DenZa-Gaussian adapts 3D Gaussian Splatting for ADF-STEM tomography by modeling scattering as a learnable scalar field, adding tilt-angle normalization, and using a Fourier amplitude loss to improve sparse-view 3D reconstructions.
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3DGR-CT: Sparse-View CT Reconstruction with a 3D Gaussian Representation
3DGR-CT adapts 3D Gaussian splatting with FBP-guided initialization and differentiable CT projection for sparse-view reconstruction, claiming better accuracy and speed than prior methods.