HAD uses multi-view reasoning from a pre-trained feedforward NVS network to estimate and mask hallucination scores in diffusion priors, reducing artifacts and achieving SOTA novel view synthesis in sparse-view 3D reconstruction.
Gaussiandreamer: Fast generation from text to 3d gaussians by bridging 2d and 3d diffusion models
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AugSplat augments Gaussian Splatting with synthetic views from a pre-trained radiance field to improve sparse-view reconstruction quality on mip-NeRF 360 scenes while keeping real-time rendering.
citing papers explorer
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HAD: Hallucination-Aware Diffusion Priors for 3D Reconstruction
HAD uses multi-view reasoning from a pre-trained feedforward NVS network to estimate and mask hallucination scores in diffusion priors, reducing artifacts and achieving SOTA novel view synthesis in sparse-view 3D reconstruction.
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AugSplat: Radiance Field-Informed Gaussian Splatting for Sparse-View Settings
AugSplat augments Gaussian Splatting with synthetic views from a pre-trained radiance field to improve sparse-view reconstruction quality on mip-NeRF 360 scenes while keeping real-time rendering.