activity
20162023
most citedEAO-SLAM: Monocular Semi-Dense Object SLAM Based on Ensemble Data Association

114 citations · 123 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CV2023★ 1 cited

BSH-Det3D: Improving 3D Object Detection with BEV Shape Heatmap

You Shen, Yunzhou Zhang, Yanmin Wu +4

The progress of LiDAR-based 3D object detection has significantly enhanced developments in autonomous driving and robotics. However, due to the limitations of LiDAR sensors, object…

cs.RO2021★ 1 cited

Accurate and Robust Object-oriented SLAM with 3D Quadric Landmark Construction in Outdoor Environment

Rui Tian, Yunzhou Zhang, Yonghui Feng +4

Object-oriented SLAM is a popular technology in autonomous driving and robotics. In this paper, we propose a stereo visual SLAM with a robust quadric landmark representation method…

cs.CV2021★ 2 cited

Accurate and Robust Scale Recovery for Monocular Visual Odometry Based on Plane Geometry

Rui Tian, Yunzhou Zhang, Delong Zhu +3

Scale ambiguity is a fundamental problem in monocular visual odometry. Typical solutions include loop closure detection and environment information mining. For applications like se…

cs.CV2020★ 2 cited

Event-VPR: End-to-End Weakly Supervised Network Architecture for Event-based Visual Place Recognition

Delei Kong, Zheng Fang, Haojia Li +3

Traditional visual place recognition (VPR) methods generally use frame-based cameras, which is easy to fail due to dramatic illumination changes or fast motions. In this paper, we…

cs.RO2020★ 114 cited

EAO-SLAM: Monocular Semi-Dense Object SLAM Based on Ensemble Data Association

Yanmin Wu, Yunzhou Zhang, Delong Zhu +3

Object-level data association and pose estimation play a fundamental role in semantic SLAM, which remain unsolved due to the lack of robust and accurate algorithms. In this work, w…

cs.CV2018★ 3 cited

PRED18: Dataset and Further Experiments with DAVIS Event Camera in Predator-Prey Robot Chasing

Diederik Paul Moeys, Daniel Neil, Federico Corradi +7

Machine vision systems using convolutional neural networks (CNNs) for robotic applications are increasingly being developed. Conventional vision CNNs are driven by camera frames at…