2 citations · 2 across the 7 of their papers we have counts for
7 papers
OptiSAR-Net++: A Large-Scale Benchmark and Transformer-Free Framework for Cross-Domain Remote Sensing Visual Grounding
Xiaoyu Tang, Jun Dong, Jintao Cheng +1
Remote sensing visual grounding (RSVG) aims to localize specific targets in remote sensing images using natural language expressions. However, existing methods are restricted to si…
A Pseudo Global Fusion Paradigm-Based Cross-View Network for LiDAR-Based Place Recognition
Jintao Cheng, Jiehao Luo, Xieyuanli Chen +4
LiDAR-based Place Recognition (LPR) remains a critical task in Embodied Artificial Intelligence (AI) and Autonomous Driving, primarily addressing localization challenges in GPS-den…
KDMOS:Knowledge Distillation for Motion Segmentation
Chunyu Cao, Jintao Cheng, Zeyu Chen +4
Motion Object Segmentation (MOS) is crucial for autonomous driving, as it enhances localization, path planning, map construction, scene flow estimation, and future state prediction…
MambaFlow: A Novel and Flow-guided State Space Model for Scene Flow Estimation
Jiehao Luo, Jintao Cheng, Xiaoyu Tang +3
Scene flow estimation aims to predict 3D motion from consecutive point cloud frames, which is of great interest in autonomous driving field. Existing methods face challenges such a…
OverlapMamba: Novel Shift State Space Model for LiDAR-based Place Recognition
Qiuchi Xiang, Jintao Cheng, Jiehao Luo +4
Place recognition is the foundation for enabling autonomous systems to achieve independent decision-making and safe operations. It is also crucial in tasks such as loop closure det…
YOLO-Ant: A Lightweight Detector via Depthwise Separable Convolutional and Large Kernel Design for Antenna Interference Source Detection
Xiaoyu Tang, Xingming Chen, Jintao Cheng +4
In the era of 5G communication, removing interference sources that affect communication is a resource-intensive task. The rapid development of computer vision has enabled unmanned…
MF-MOS: A Motion-Focused Model for Moving Object Segmentation
Jintao Cheng, Kang Zeng, Zhuoxu Huang +5
Moving object segmentation (MOS) provides a reliable solution for detecting traffic participants and thus is of great interest in the autonomous driving field. Dynamic capture is a…