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+### GaussianPro: 3D Gaussian Splatting with Progressive Propagation
+This method generates depth and normal maps that guide the growth and adjustment of Gaussians. It employs patch matching to propagate depth and normal information from neighboring pixels to generate new values. Geometric filtering and selection then identify pixels needing additional Gaussians, which are initialized using the propagated information. It also introduces a planar loss to ensure Gaussians match real surfaces more closely. This method enforces consistency between the Gaussian's rendered normal and the propagated normal using L1 and angular loss.