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By intelligently fusing semantic and geometric priors with rendering residuals, this method achieves state-of-the-art novel view synthesis from sparse inputs, outperforming methods relying solely on photometric error.
Achieve high-fidelity 3D human rendering from a single image by distilling priors from a multi-view diffusion model into 3D Gaussians, outperforming prior single-view reconstruction methods.
