GazePrior learns a 3D prior over eyes to synthesize realistic ground-truth data for training eye trackers on new devices without new real data collection.
Instant neural graphics primitives with a multiresolution hash encoding.ACM transactions on graphics (TOG), 41(4):1–15
4 Pith papers cite this work. Polarity classification is still indexing.
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SplitGS-Loc disambiguates 2D-3D correspondences in photometrically optimized GSFFs via Mixture-of-Gaussians splitting and multi-view consistency selection, yielding stable PnP and SOTA localization results.
PEPS decomposes positional encodings into projected points with unique frequency-dependent motions to support more efficient learned grid-based encodings in INRs, outperforming prior methods on image, texture, and SDF tasks with often 25% fewer parameters.
A quota-governor for Gaussian Splatting that tracks a quadratic target point count by adjusting existing hyperparameters, reaching the target by 15k iterations without hard cutoffs for fairer evaluations.
citing papers explorer
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GazePrior: Zero-Shot AR/VR Eye Tracking via Learned 3D Gaze Reconstruction
GazePrior learns a 3D prior over eyes to synthesize realistic ground-truth data for training eye trackers on new devices without new real data collection.
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Disambiguating 2D-3D Correspondences in Gaussian Splatting-based Feature Fields for Visual Localization
SplitGS-Loc disambiguates 2D-3D correspondences in photometrically optimized GSFFs via Mixture-of-Gaussians splitting and multi-view consistency selection, yielding stable PnP and SOTA localization results.
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PEPS: Positional Encoding Projected Sampling -- Extended
PEPS decomposes positional encodings into projected points with unique frequency-dependent motions to support more efficient learned grid-based encodings in INRs, outperforming prior methods on image, texture, and SDF tasks with often 25% fewer parameters.
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Smart target point control for Gaussian Splatting methods
A quota-governor for Gaussian Splatting that tracks a quadratic target point count by adjusting existing hyperparameters, reaching the target by 15k iterations without hard cutoffs for fairer evaluations.