Publications (7)
CDFormer: Cross-Domain Few-Shot Object Detection Transformer Against Feature Confusion
Boyuan Meng, Xiaohan Zhang, Peilin Li +5
Cross-domain few-shot object detection (CD-FSOD) aims to detect novel objects across different domains with limited class instances. Feature confusion, including object-background…
S-BEVLoc: BEV-based Self-supervised Framework for Large-scale LiDAR Global Localization
Chenghao Zhang, Lun Luo, Si-Yuan Cao +6
LiDAR-based global localization is an essential component of simultaneous localization and mapping (SLAM), which helps loop closure and re-localization. Current approaches rely on…
Boosting Instance Awareness via Cross-View Correlation with 4D Radar and Camera for 3D Object Detection
Xiaokai Bai, Lianqing Zheng, Si-Yuan Cao +6
4D millimeter-wave radar has emerged as a promising sensing modality for autonomous driving due to its robustness and affordability. However, its sparse and weak geometric cues mak…
SCPNet: Unsupervised Cross-modal Homography Estimation via Intra-modal Self-supervised Learning
Runmin Zhang, Jun Ma, Si-Yuan Cao +5
We propose a novel unsupervised cross-modal homography estimation framework based on intra-modal Self-supervised learning, Correlation, and consistent feature map Projection, namel…
BEVPlace: Learning LiDAR-based Place Recognition using Bird's Eye View Images
Lun Luo, Shuhang Zheng, Yixuan Li +4
Place recognition is a key module for long-term SLAM systems. Current LiDAR-based place recognition methods usually use representations of point clouds such as unordered points or…
I2P-Rec: Recognizing Images on Large-scale Point Cloud Maps through Bird's Eye View Projections
Shuhang Zheng, Yixuan Li, Zhu Yu +8
Place recognition is an important technique for autonomous cars to achieve full autonomy since it can provide an initial guess to online localization algorithms. Although current m…