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From the 1 of 9 linked papers with an AI index.

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20242026
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10 papers

cs.CV2026

RoGS: Adaptive Meshgrid Gaussian for Large-Scale Road Surface Mapping

Tianchen Deng, Zhiheng Feng, Wenhua Wu +4

The paper presents ROADGS-T, a framework that uses adaptive meshgrid Gaussian surfels to efficiently reconstruct large‑scale road surfaces for autonomous driving, improving detail…

cs.CV2026

WeatherCity: Urban Scene Reconstruction with Controllable Multi-Weather Transformation

Wenhua Wu, Huai Guan, Zhe Liu +1

Editable high-fidelity 4D scenes are crucial for autonomous driving, as they can be applied to end-to-end training and closed-loop simulation. However, existing reconstruction meth…

cs.CV2026

CAD-SLAM: Consistency-Aware Dynamic SLAM with Dynamic-Static Decoupled Mapping

Wenhua Wu, Chenpeng Su, Siting Zhu +6

Recent advances in neural radiation fields (NeRF) and 3D Gaussian-based SLAM have achieved impressive localization accuracy and high-quality dense mapping in static scenes. However…

cs.CV2026

VPGS-SLAM: Voxel-based Progressive 3D Gaussian SLAM in Large-Scale Scenes

Tianchen Deng, Wenhua Wu, Junjie He +4

3D Gaussian Splatting has recently shown promising results in dense visual SLAM. However, existing 3DGS-based SLAM methods are all constrained to small-room scenarios and struggle…

cs.CV2025

Reloc-VGGT: Visual Re-localization with Geometry Grounded Transformer

Tianchen Deng, Wenhua Wu, Kunzhen Wu +7

Visual localization has traditionally been formulated as a pair-wise pose regression problem. Existing approaches mainly estimate relative poses between two images and employ a lat…

cs.RO2025

DGSLAM: 4D Dynamic Gaussian Splatting SLAM

Siting Zhu, Yuxiang Huang, Wenhua Wu +4

Recent advances in Dense Simultaneous Localization and Mapping (SLAM) have demonstrated remarkable performance in static environments. However, dense SLAM in dynamic environments r…