Lingxiang Hu — accepted AI-conference papers

2026

EC3R-SLAM: Efficient and Consistent Monocular Dense SLAM with Feed-Forward 3D Reconstruction

Lingxiang Hu, Naima Ait Oufroukh, Fabien Bonardi, Ghandour Raymond

ICRA 2026poster

The application of monocular dense Simultaneous Localization and Mapping (SLAM) is often hindered by high latency, large GPU memory consumption, and reliance on camera calibration. To relax this constraint, we propose EC3R-SLAM, a novel calibration-free monocular dense SLAM framework that jointly ac…

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2025

DPR-Splat: Depth and Pose Refinement with Sparse-View 3D Gaussian Splatting for Novel View Synthesis

Lingxiang Hu, Zhiheng Li, Xingfei Zhu, Dun Li, Ran Song

IROS 2025

Recent advances in 3D Gaussian Splatting have demonstrated impressive performance in novel view synthesis, particularly with dense image sets. However, its performance degrades significantly in sparse-view scenarios, primarily due to the challenge of obtaining accurate camera poses. Also, achieving

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