4 citations · 7 across the 5 of their papers we have counts for
5 papers
CoMo3R-SLAM: Collaborative Monocular Dense SLAM with Learned 3D Reconstruction Priors for Outdoor Multi-Agent Systems
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Outdoor robot teams need a shared dense map despite limited overlap, independent reference frames, and uncertain monocular scale. Collaborative dense SLAM systems typically resolve…
MAGS-SLAM: Monocular Multi-Agent Gaussian Splatting SLAM for Geometrically and Photometrically Consistent Reconstruction
Zhihao Cao, Qi Shao, Shuhao Zhai +4
Collaborative photorealistic 3D reconstruction from multiple agents enables rapid large-scale scene capture for virtual production and cooperative multi-robot exploration. While re…
MCGS-SLAM: A Multi-Camera SLAM Framework Using Gaussian Splatting for High-Fidelity Mapping
Zhihao Cao, Hanyu Wu, Li Wa Tang +5
Recent progress in dense SLAM has primarily targeted monocular setups, often at the expense of robustness and geometric coverage. We present MCGS-SLAM, the first purely RGB-based m…
Simple But Effective: Rethinking the Ability of Deep Learning in fNIRS to Exclude Abnormal Input
Zhihao Cao
Functional near-infrared spectroscopy (fNIRS) is a non-invasive technique for monitoring brain activity. To better understand the brain, researchers often use deep learning to addr…
Calibration of Deep Learning Classification Models in fNIRS
Zhihao Cao, Zizhou Luo
Functional near-infrared spectroscopy (fNIRS) is a valuable non-invasive tool for monitoring brain activity. The classification of fNIRS data in relation to conscious activity hold…