SVGS improves Gaussian Splatting novel-view synthesis by replacing single-color primitives with spatially varying color and opacity functions implemented via bilinear interpolation, movable kernels, or tiny neural networks on 2D Gaussian surfels.
The unreasonable effectiveness of deep features as a perceptual metric
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Latent-space hierarchical diffusion models with targeted error-correction techniques generate realistic videos exceeding 1000 frames while using less compute than prior pixel-space approaches.
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SVGS: Enhancing Gaussian Splatting Using Primitives with Spatially Varying Colors
SVGS improves Gaussian Splatting novel-view synthesis by replacing single-color primitives with spatially varying color and opacity functions implemented via bilinear interpolation, movable kernels, or tiny neural networks on 2D Gaussian surfels.
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Latent Video Diffusion Models for High-Fidelity Long Video Generation
Latent-space hierarchical diffusion models with targeted error-correction techniques generate realistic videos exceeding 1000 frames while using less compute than prior pixel-space approaches.