AvatarPointillist autoregressively generates adaptive 3D point clouds via Transformer for photorealistic 4D Gaussian avatars from one image, jointly predicting animation bindings and using a conditioned Gaussian decoder.
Headgap: Few-shot 3d head avatar via generalizable gaussian priors
4 Pith papers cite this work. Polarity classification is still indexing.
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cs.CV 4years
2026 4representative citing papers
VRGaussianAvatar enables real-time full-body 3D Gaussian Splatting avatars in VR from HMD tracking alone via inverse kinematics and binocular batching for efficient stereo rendering, outperforming mesh baselines in performance and user ratings.
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.
SAGE self-learns Gaussian expression deformations via joint surfel-SDF optimization and self-supervised consistency, enabling comparable avatar quality from single frames, monocular rotations, or one-shot inputs.
citing papers explorer
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AvatarPointillist: AutoRegressive 4D Gaussian Avatarization
AvatarPointillist autoregressively generates adaptive 3D point clouds via Transformer for photorealistic 4D Gaussian avatars from one image, jointly predicting animation bindings and using a conditioned Gaussian decoder.
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VRGaussianAvatar: Integrating 3D Gaussian Avatars into VR
VRGaussianAvatar enables real-time full-body 3D Gaussian Splatting avatars in VR from HMD tracking alone via inverse kinematics and binocular batching for efficient stereo rendering, outperforming mesh baselines in performance and user ratings.
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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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Self-Learning Expression Deformations for Data-Efficient Gaussian Avatars
SAGE self-learns Gaussian expression deformations via joint surfel-SDF optimization and self-supervised consistency, enabling comparable avatar quality from single frames, monocular rotations, or one-shot inputs.