no code implementations • 21 Apr 2023 • Yuxuan Liu, Zhenhua Xu, Huaiyang Huang, Lujia Wang, Ming Liu
Predicting accurate depth with monocular images is important for low-cost robotic applications and autonomous driving.
1 code implementation • 18 Jul 2021 • Peide Cai, Hengli Wang, Huaiyang Huang, Yuxuan Liu, Ming Liu
In this work, we present a general deep imitative reinforcement learning approach (DIRL), which successfully achieves agile autonomous racing using visual inputs.
1 code implementation • 20 Apr 2021 • Jianhao Jiao, Huaiyang Huang, Liang Li, Zhijian He, Yilong Zhu, Ming Liu
This paper investigates two typical image-type representations for event camera-based tracking: time surface (TS) and event map (EM).
no code implementations • 8 Apr 2021 • Haoyang Ye, Huaiyang Huang, Marco Hutter, Timothy Sandy, Ming Liu
In this paper, we introduce a method for visual relocalization using the geometric information from a 3D surfel map.
no code implementations • 24 Mar 2021 • Jianhao Jiao, Yilong Zhu, Haoyang Ye, Huaiyang Huang, Peng Yun, Linxin Jiang, Lujia Wang, Ming Liu
Modern LiDAR-SLAM (L-SLAM) systems have shown excellent results in large-scale, real-world scenarios.
1 code implementation • 9 Nov 2020 • Huaiyang Huang, Haoyang Ye, Jianhao Jiao, Yuxiang Sun, Ming Liu
To take the advantages of both, in this work, we present a complete visual inertial localization system based on a hybrid map representation to reduce the computational cost and increase the positioning accuracy.
no code implementations • 21 Aug 2020 • Hengli Wang, Yuxuan Liu, Huaiyang Huang, Yuheng Pan, Wenbin Yu, Jialin Jiang, Dianbin Lyu, Mohammud J. Bocus, Ming Liu, Ioannis Pitas, Rui Fan
In this paper, we introduce a novel suspect-and-investigate framework, which can be easily embedded in a drone for automated parking violation detection (PVD).
1 code implementation • 24 Jun 2020 • Huaiyang Huang, Haoyang Ye, Yuxiang Sun, Ming Liu
Incorporating prior structure information into the visual state estimation could generally improve the localization performance.
2 code implementations • 17 May 2020 • Rui Fan, Hengli Wang, Bohuan Xue, Huaiyang Huang, YuAn Wang, Ming Liu, Ioannis Pitas
To evaluate the performance of our proposed SNE, we created three large-scale synthetic datasets (easy, medium and hard) using 24 3D mesh models, each of which is used to generate 1800--2500 pairs of depth images (resolution: 480X640 pixels) and the corresponding ground-truth surface normal maps from different views.
no code implementations • 16 Apr 2020 • Tianyu Liu, Qinghai Liao, Lu Gan, Fulong Ma, Jie Cheng, Xupeng Xie, Zhe Wang, Yingbing Chen, Yilong Zhu, Shuyang Zhang, Zhengyong Chen, Yang Liu, Meng Xie, Yang Yu, Zitong Guo, Guang Li, Peidong Yuan, Dong Han, Yuying Chen, Haoyang Ye, Jianhao Jiao, Peng Yun, Zhenhua Xu, Hengli Wang, Huaiyang Huang, Sukai Wang, Peide Cai, Yuxiang Sun, Yandong Liu, Lujia Wang, Ming Liu
Moreover, many countries have imposed tough lockdown measures to reduce the virus transmission (e. g., retail, catering) during the pandemic, which causes inconveniences for human daily life.
no code implementations • 23 Feb 2020 • Haoyang Ye, Huaiyang Huang, Ming Liu
The tracked points with and without the global planar information involve both global and local constraints of frames to the system.
no code implementations • 29 Oct 2019 • Huaiyang Huang, Rui Fan, Yilong Zhu, Ming Liu, Ioannis Pitas
Pavement condition is crucial for civil infrastructure maintenance.
no code implementations • 12 Apr 2019 • Rui Fan, Jianhao Jiao, Jie Pan, Huaiyang Huang, Shaojie Shen, Ming Liu
This makes the damaged road areas more distinguishable from the road surface.