A variance-aware conditional MLP operating on 3D Gaussians corrects semantic errors from multi-view inconsistent 2D features to produce more accurate and robust 3D semantic Gaussian Splatting.
Cf3: Compact and fast 3d feature fields
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C3G creates compact 3D Gaussian representations with 2K points by guiding placement via learnable tokens that aggregate multi-view features through attention, yielding better efficiency and performance than dense methods.
citing papers explorer
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NRGS: Neural Regularization for Robust 3D Semantic Gaussian Splatting
A variance-aware conditional MLP operating on 3D Gaussians corrects semantic errors from multi-view inconsistent 2D features to produce more accurate and robust 3D semantic Gaussian Splatting.
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C3G: Learning Compact 3D Representations with 2K Gaussians
C3G creates compact 3D Gaussian representations with 2K points by guiding placement via learnable tokens that aggregate multi-view features through attention, yielding better efficiency and performance than dense methods.