30 citations · 58 across the 17 of their papers we have counts for
9 papers · 1 filter
RING#: PR-by-PE Global Localization with Roto-translation Equivariant Gram Learning
Sha Lu, Xuecheng Xu, Yuxuan Wu +4
Global localization using onboard perception sensors, such as cameras and LiDARs, is crucial in autonomous driving and robotics applications when GPS signals are unreliable. Most a…
Leveraging BEV Representation for 360-degree Visual Place Recognition
Xuecheng Xu, Yanmei Jiao, Sha Lu +3
This paper investigates the advantages of using Bird's Eye View (BEV) representation in 360-degree visual place recognition (VPR). We propose a novel network architecture that util…
DeepRING: Learning Roto-translation Invariant Representation for LiDAR based Place Recognition
Sha Lu, Xuecheng Xu, Li Tang +2
LiDAR based place recognition is popular for loop closure detection and re-localization. In recent years, deep learning brings improvements to place recognition by learnable featur…
DPCN++: Differentiable Phase Correlation Network for Versatile Pose Registration
Zexi Chen, Yiyi Liao, Haozhe Du +5
Pose registration is critical in vision and robotics. This paper focuses on the challenging task of initialization-free pose registration up to 7DoF for homogeneous and heterogeneo…
Learn to Differ: Sim2Real Small Defection Segmentation Network
Zexi Chen, Zheyuan Huang, Yunkai Wang +3
Recent studies on deep-learning-based small defection segmentation approaches are trained in specific settings and tend to be limited by fixed context. Throughout the training, the…
Radar-to-Lidar: Heterogeneous Place Recognition via Joint Learning
Huan Yin, Xuecheng Xu, Yue Wang +1
Place recognition is critical for both offline mapping and online localization. However, current single-sensor based place recognition still remains challenging in adverse conditio…
CORAL: Colored structural representation for bi-modal place recognition
Yiyuan Pan, Xuecheng Xu, Weijie Li +3
Place recognition is indispensable for a drift-free localization system. Due to the variations of the environment, place recognition using single-modality has limitations. In this…
PREGAN: Pose Randomization and Estimation for Weakly Paired Image Style Translation
Zexi Chen, Jiaxin Guo, Xuecheng Xu +3
Utilizing the trained model under different conditions without data annotation is attractive for robot applications. Towards this goal, one class of methods is to translate the ima…
Deep Phase Correlation for End-to-End Heterogeneous Sensor Measurements Matching
Zexi Chen, Xuecheng Xu, Yue Wang +1
The crucial step for localization is to match the current observation to the map. When the two sensor modalities are significantly different, matching becomes challenging. In this…