TokenGS uses learnable Gaussian tokens in an encoder-decoder architecture to regress 3D means directly, achieving SOTA feed-forward reconstruction on static and dynamic scenes with better robustness.
Nerf: Representing scenes as neural radiance fields for view syn- thesis.Communications of the ACM, 65(1):99–106, 2021
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AGILE generates complete object meshes via VLM-guided synthesis and tracks poses with anchor-and-track plus contact-aware optimization to achieve robust hand-object reconstruction from video.
GaussianDWM uses 3D Gaussians with embedded linguistic features, language-guided sampling, and dual-condition generation for unified scene understanding and multi-modal output in driving world models.
F3G-Avatar improves full-body Gaussian avatars by adding a dedicated face-focused deformation branch to better preserve facial geometry and expressions from multi-view RGB video.
citing papers explorer
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TokenGS: Decoupling 3D Gaussian Prediction from Pixels with Learnable Tokens
TokenGS uses learnable Gaussian tokens in an encoder-decoder architecture to regress 3D means directly, achieving SOTA feed-forward reconstruction on static and dynamic scenes with better robustness.
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AGILE: Hand-Object Interaction Reconstruction from Video via Agentic Generation
AGILE generates complete object meshes via VLM-guided synthesis and tracks poses with anchor-and-track plus contact-aware optimization to achieve robust hand-object reconstruction from video.
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GaussianDWM: 3D Gaussian Driving World Model for Unified Scene Understanding and Multi-Modal Generation
GaussianDWM uses 3D Gaussians with embedded linguistic features, language-guided sampling, and dual-condition generation for unified scene understanding and multi-modal output in driving world models.
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F3G-Avatar : Face Focused Full-body Gaussian Avatar
F3G-Avatar improves full-body Gaussian avatars by adding a dedicated face-focused deformation branch to better preserve facial geometry and expressions from multi-view RGB video.