UIKA is a feed-forward animatable Gaussian head model using UV-guided correspondence estimation and learnable UV tokens with dual-level attention, trained on large-scale synthetic data to handle pose-free inputs.
Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106
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GOR-IS removes objects from 3D Gaussian Splatting reconstructions by performing inpainting in an intrinsic decomposition space that explicitly models light transport for consistent global lighting and non-Lambertian surfaces.
The paper reformulates absolute pose regression as regressing disentangled world-coordinate raymaps and pointmaps from images, then recovering pose via a differentiable solver, claiming SOTA results on 7-Scenes and Cambridge Landmarks.
citing papers explorer
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UIKA: Fast Universal Head Avatar from Pose-Free Images
UIKA is a feed-forward animatable Gaussian head model using UV-guided correspondence estimation and learnable UV tokens with dual-level attention, trained on large-scale synthetic data to handle pose-free inputs.
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GOR-IS: 3D Gaussian Object Removal in the Intrinsic Space
GOR-IS removes objects from 3D Gaussian Splatting reconstructions by performing inpainting in an intrinsic decomposition space that explicitly models light transport for consistent global lighting and non-Lambertian surfaces.
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GRLoc: Geometric Representation Regression for Visual Localization
The paper reformulates absolute pose regression as regressing disentangled world-coordinate raymaps and pointmaps from images, then recovering pose via a differentiable solver, claiming SOTA results on 7-Scenes and Cambridge Landmarks.