24 citations · 49 across the 6 of their papers we have counts for
8 papers
Semantic Segmentation-assisted Scene Completion for LiDAR Point Clouds
Xuemeng Yang, Hao Zou, Xin Kong +5
Outdoor scene completion is a challenging issue in 3D scene understanding, which plays an important role in intelligent robotics and autonomous driving. Due to the sparsity of LiDA…
SSC: Semantic Scan Context for Large-Scale Place Recognition
Lin Li, Xin Kong, Xiangrui Zhao +2
Place recognition gives a SLAM system the ability to correct cumulative errors. Unlike images that contain rich texture features, point clouds are almost pure geometric information…
SA-LOAM: Semantic-aided LiDAR SLAM with Loop Closure
Lin Li, Xin Kong, Xiangrui Zhao +4
LiDAR-based SLAM system is admittedly more accurate and stable than others, while its loop closure detection is still an open issue. With the development of 3D semantic segmentatio…
HR-Depth: High Resolution Self-Supervised Monocular Depth Estimation
Xiaoyang Lyu, Liang Liu, Mengmeng Wang +5
Self-supervised learning shows great potential in monoculardepth estimation, using image sequences as the only source ofsupervision. Although people try to use the high-resolutioni…
FlowMOT: 3D Multi-Object Tracking by Scene Flow Association
Guangyao Zhai, Xin Kong, Jinhao Cui +2
Most end-to-end Multi-Object Tracking (MOT) methods face the problems of low accuracy and poor generalization ability. Although traditional filter-based methods can achieve better…
F-Siamese Tracker: A Frustum-based Double Siamese Network for 3D Single Object Tracking
Hao Zou, Jinhao Cui, Xin Kong +4
This paper presents F-Siamese Tracker, a novel approach for single object tracking prominently characterized by more robustly integrating 2D and 3D information to reduce redundant…