activity
20212023
most citedS-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

7 citations · 12 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CV2023

Informative Data Selection with Uncertainty for Multi-modal Object Detection

Xinyu Zhang, Zhiwei Li, Zhenhong Zou +5

Noise has always been nonnegligible trouble in object detection by creating confusion in model reasoning, thereby reducing the informativeness of the data. It can lead to inaccurat…

cs.CV2022

CAMO-MOT: Combined Appearance-Motion Optimization for 3D Multi-Object Tracking with Camera-LiDAR Fusion

Li Wang, Xinyu Zhang, Wenyuan Qin +7

3D Multi-object tracking (MOT) ensures consistency during continuous dynamic detection, conducive to subsequent motion planning and navigation tasks in autonomous driving. However,…

cs.RO2022

Intelligent Amphibious Ground-Aerial Vehicles: State of the Art Technology for Future Transportation

Xinyu Zhang, Jiangeng Huang, Yuanhao Huang +7

Amphibious ground-aerial vehicles fuse flying and driving modes to enable more flexible air-land mobility and have received growing attention recently. By analyzing the existing am…

cs.RO2022★ 1 cited

Dynamic Registration: Joint Ego Motion Estimation and 3D Moving Object Detection in Dynamic Environment

Wenyu Li, Xinyu Zhang, Zijun Wang +3

Localization in a dynamic environment suffers from moving objects. Removing dynamic object is crucial in this situation but become tricky when ego-motion is coupled. In this paper,…

cs.CV2021★ 1 cited

Lite-FPN for Keypoint-based Monocular 3D Object Detection

Lei Yang, Xinyu Zhang, Li Wang +2

3D object detection with a single image is an essential and challenging task for autonomous driving. Recently, keypoint-based monocular 3D object detection has made tremendous prog…

cs.CV2021★ 2 cited

IPS300+: a Challenging Multimodal Dataset for Intersection Perception System

Huanan Wang, Xinyu Zhang, Jun Li +4

Due to the high complexity and occlusion, insufficient perception in the crowded urban intersection can be a serious safety risk for both human drivers and autonomous algorithms, w…

cs.CV2021★ 1 cited

A novel multimodal fusion network based on a joint coding model for lane line segmentation

Zhenhong Zou, Xinyu Zhang, Huaping Liu +3

There has recently been growing interest in utilizing multimodal sensors to achieve robust lane line segmentation. In this paper, we introduce a novel multimodal fusion architectur…

cs.CV2021★ 7 cited

S-AT GCN: Spatial-Attention Graph Convolution Network based Feature Enhancement for 3D Object Detection

Li Wang, Chenfei Wang, Xinyu Zhang +2

3D object detection plays a crucial role in environmental perception for autonomous vehicles, which is the prerequisite of decision and control. This paper analyses partition-based…