Qingxiao Wu — accepted AI-conference papers

2026

UNITE-NBV: Uncertainty-Driven and Information-Enhanced Gain Estimation for Next Best View

Kaice Jiang, Qingxiao Wu, Sicong Li, Feng Zhu, Yingjian Fang, Jianxin Cai

RA-L 2026

Next Best View (NBV) algorithms are a critical area of research in 3D reconstruction. They aim to efficiently reconstruct 3D scenes by maximizing information gain from the next optimal viewpoint. However, current NBV methods often neglect the importance of high-quality candidate view sampling, leadi

Cited by 0 Source ↗Scholar ↗

2023

BoW3D: Bag of Words for Real-Time Loop Closing in 3D LiDAR SLAM

Yunge Cui, Xieyuanli Chen, Yinlong Zhang, Jiahua Dong, Qingxiao Wu, Feng Zhu

RA-L 2023

Loop closing is a fundamental part of simultaneous localization and mapping (SLAM) for autonomous mobile systems. In the field of visual SLAM, bag of words (BoW) has achieved great success in loop closure. The BoW features for loop searching can also be used in the subsequent 6-DoF loop correction.

Cited by 99 Source ↗code ↗Scholar ↗