ConFixGS repairs feedforward 3D Gaussian Splatting with confidence-aware diffusion priors, delivering up to 3.68 dB PSNR gains and halved FID scores on Waymo, nuScenes, and KITTI novel view synthesis tasks.
Gsfixer: Improving 3d gaussian splatting with reference-guided video diffusion priors
8 Pith papers cite this work. Polarity classification is still indexing.
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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.
GeoQuery replaces corrupted rendering features with geometry-aligned proxy queries and restricts cross-view attention to local windows, enabling robust diffusion-based refinement under extreme view sparsity.
VidSplat iteratively synthesizes novel views with geometry-guided video diffusion to enable robust Gaussian splatting reconstruction from sparse or single-image inputs.
ArtifactWorld restores artifacts in 3D Gaussian Splatting by training a video diffusion backbone on 107.5K paired clips with an isomorphic predictor for artifact heatmaps and an Artifact-Aware Triplet Fusion mechanism to achieve better sparse-view novel synthesis.
A technique reconstructs large urban areas from sparse extreme off-nadir satellite images by modeling geometry as a Z-monotonic 2.5D height map SDF and applying a generative network to restore plausible textures on the resulting mesh.
Pantheon360 introduces a controllable 360° video diffusion framework that uses an explicit 3D cache from sparse inputs to enforce geometric consistency for digital twin generation.
A 3D Gaussian Splatting pipeline that uses a mask-aware one-step diffusion refiner, opacity-driven Gaussian densification, and LoRA/SDS regularization to do few-shot novel-view synthesis on unconstrained images with distractors.
citing papers explorer
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ConFixGS: Learning to Fix Feedforward 3D Gaussian Splatting with Confidence-Aware Diffusion Priors in Driving Scenes
ConFixGS repairs feedforward 3D Gaussian Splatting with confidence-aware diffusion priors, delivering up to 3.68 dB PSNR gains and halved FID scores on Waymo, nuScenes, and KITTI novel view synthesis tasks.
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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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GeoQuery: Geometry-Query Diffusion for Sparse-View Reconstruction
GeoQuery replaces corrupted rendering features with geometry-aligned proxy queries and restricts cross-view attention to local windows, enabling robust diffusion-based refinement under extreme view sparsity.
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VidSplat: Gaussian Splatting Reconstruction with Geometry-Guided Video Diffusion Priors
VidSplat iteratively synthesizes novel views with geometry-guided video diffusion to enable robust Gaussian splatting reconstruction from sparse or single-image inputs.
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ArtifactWorld: Scaling 3D Gaussian Splatting Artifact Restoration via Video Generation Models
ArtifactWorld restores artifacts in 3D Gaussian Splatting by training a video diffusion backbone on 107.5K paired clips with an isomorphic predictor for artifact heatmaps and an Artifact-Aware Triplet Fusion mechanism to achieve better sparse-view novel synthesis.
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From Orbit to Ground: Generative City Photogrammetry from Extreme Off-Nadir Satellite Images
A technique reconstructs large urban areas from sparse extreme off-nadir satellite images by modeling geometry as a Z-monotonic 2.5D height map SDF and applying a generative network to restore plausible textures on the resulting mesh.
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Pantheon360: Taming Digital Twin Generation via 3D-Aware 360{\deg} Video Diffusion
Pantheon360 introduces a controllable 360° video diffusion framework that uses an explicit 3D cache from sparse inputs to enforce geometric consistency for digital twin generation.
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Difix3D-W: Distractor-Free Few-Shot 3D Gaussian Splatting in the Wild
A 3D Gaussian Splatting pipeline that uses a mask-aware one-step diffusion refiner, opacity-driven Gaussian densification, and LoRA/SDS regularization to do few-shot novel-view synthesis on unconstrained images with distractors.