4 papers
MASt3R-Fusion: Integrating Feed-Forward Visual Model with IMU, GNSS for High-Functionality SLAM
Yuxuan Zhou, Xingxing Li, Shengyu Li +3
Visual SLAM is a cornerstone technique in robotics, autonomous driving and extended reality (XR), yet classical systems often struggle with low-texture environments, scale ambiguit…
S3MOT: Monocular 3D Object Tracking with Selective State Space Model
Zhuohao Yan, Shaoquan Feng, Xingxing Li +3
Accurate and reliable multi-object tracking (MOT) in 3D space is essential for advancing robotics and computer vision applications. However, it remains a significant challenge in m…
SF-Loc: A Visual Mapping and Geo-Localization System based on Sparse Visual Structure Frames
Yuxuan Zhou, Xingxing Li, Shengyu Li +3
For high-level geo-spatial applications and intelligent robotics, accurate global pose information is of crucial importance. Map-aided localization is a universal approach to overc…
DBA-Fusion: Tightly Integrating Deep Dense Visual Bundle Adjustment with Multiple Sensors for Large-Scale Localization and Mapping
Yuxuan Zhou, Xingxing Li, Shengyu Li +3
Visual simultaneous localization and mapping (VSLAM) has broad applications, with state-of-the-art methods leveraging deep neural networks for better robustness and applicability.…