BEA-GS achieves superior object boundary segmentation in 3D Gaussian Splatting by introducing two new losses that adjust geometry of visible and non-visible Gaussians based on semantics.
Langsplat: 3d language gaussian splatting
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ULF-Loc removes bias from 3DGS landmark features via geometry-weighted fusion and consistency checks, cutting median translation error 17% while using 1/10 training time and 1/6 GPU memory of prior state-of-the-art.
PAGaS refines multi-view stereo depths by optimizing 1DoF Gaussians whose positions and sizes are fixed by back-projected pixel volumes, producing detailed depth maps that outperform reference baselines on 3D reconstruction benchmarks.
RiGS decomposes scenes into static, rigid, and transient 4D Gaussians with an object-wise dynamic mask and scene flow guidance to model multi-scale motions and achieve SOTA novel view synthesis.
A scene-agnostic object codebook learned via unsupervised object-centric learning provides consistent identity-anchored representations for 3D Gaussians across multiple scenes.
citing papers explorer
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BEA-GS: BEyond RAdiance Supervision in 3DGS for Precise Object Extraction
BEA-GS achieves superior object boundary segmentation in 3D Gaussian Splatting by introducing two new losses that adjust geometry of visible and non-visible Gaussians based on semantics.
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ULF-Loc: Unbiased Landmark Feature for Robust Visual Localization with 3D Gaussian Splatting
ULF-Loc removes bias from 3DGS landmark features via geometry-weighted fusion and consistency checks, cutting median translation error 17% while using 1/10 training time and 1/6 GPU memory of prior state-of-the-art.
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PAGaS: Pixel-Aligned 1DoF Gaussian Splatting for Depth Refinement
PAGaS refines multi-view stereo depths by optimizing 1DoF Gaussians whose positions and sizes are fixed by back-projected pixel volumes, producing detailed depth maps that outperform reference baselines on 3D reconstruction benchmarks.
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RiGS: Rigid-aware 4D Gaussian Splatting from a Single Monocular Video
RiGS decomposes scenes into static, rigid, and transient 4D Gaussians with an object-wise dynamic mask and scene flow guidance to model multi-scale motions and achieve SOTA novel view synthesis.
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Scene-Agnostic Object-Centric Representation Learning for 3D Gaussian Splatting
A scene-agnostic object codebook learned via unsupervised object-centric learning provides consistent identity-anchored representations for 3D Gaussians across multiple scenes.