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.
What uncertainties do we need in bayesian deep learning for computer vision?Advances in neural information processing systems, 30
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ConformaDecompose decomposes conformal prediction uncertainty by progressively localizing calibration sets, revealing reducible epistemic components that align with model limitations across tasks.
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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ConformaDecompose: Explaining Uncertainty via Calibration Localization
ConformaDecompose decomposes conformal prediction uncertainty by progressively localizing calibration sets, revealing reducible epistemic components that align with model limitations across tasks.