A method to construct propagation-consistent wireless environment digital twins from sparse CSI by creating a geometry-prior Bayesian channel map and calibrating a scene-level EM property field via differentiable ray tracing.
3d gaussian splatting for real-time radiance field rendering
5 Pith papers cite this work. Polarity classification is still indexing.
5
Pith papers citing it
citation-role summary
background 1
citation-polarity summary
years
2026 5roles
background 1polarities
background 1representative citing papers
GaussLock embeds traps targeting position, scale, rotation, opacity, and color in 3D Gaussian models to degrade unauthorized fine-tunes while preserving authorized performance.
A hybrid structural latent points representation is learned by inserting a point-wise latent VAE into a point-cloud autoencoder and regularizing toward a Gaussian prior, paired with a lightweight 3DGS rendering pipeline, yielding gains on RLBench and ManiSkill2 benchmarks.
A surface extraction framework reduces the navigation state space by over 80% while achieving 100% planning success and sub-millisecond A* searches in Matterport3D and PCT scenes.
ReefMapGS closes the loop between multimodal SLAM and 3D Gaussian Splatting to deliver COLMAP-free incremental 3D reconstruction and improved AUV trajectory estimates for underwater reef surveys up to 700 m.
citing papers explorer
-
Propagation-Consistent Wireless Environment Digital Twin Construction Under Sparse Measurements
A method to construct propagation-consistent wireless environment digital twins from sparse CSI by creating a geometry-prior Bayesian channel map and calibrating a scene-level EM property field via differentiable ray tracing.
-
Immunizing 3D Gaussian Generative Models Against Unauthorized Fine-Tuning via Attribute-Space Traps
GaussLock embeds traps targeting position, scale, rotation, opacity, and color in 3D Gaussian models to degrade unauthorized fine-tunes while preserving authorized performance.
-
Learning Structural Latent Points for Efficient Visual Representations in Robotic Manipulation
A hybrid structural latent points representation is learned by inserting a point-wise latent VAE into a point-cloud autoencoder and regularizing toward a Gaussian prior, paired with a lightweight 3DGS rendering pipeline, yielding gains on RLBench and ManiSkill2 benchmarks.
-
Beyond Geometry: Efficient Topologically-Grounded Navigation in Complex 3D Environments
A surface extraction framework reduces the navigation state space by over 80% while achieving 100% planning success and sub-millisecond A* searches in Matterport3D and PCT scenes.
-
ReefMapGS: Enabling Large-Scale Underwater Reconstruction by Closing the Loop Between Multimodal SLAM and Gaussian Splatting
ReefMapGS closes the loop between multimodal SLAM and 3D Gaussian Splatting to deliver COLMAP-free incremental 3D reconstruction and improved AUV trajectory estimates for underwater reef surveys up to 700 m.