no code implementations • 18 Mar 2024 • Zewen Xu, Yijia He, Hao Wei, Bo Xu, BinJian Xie, Yihong Wu
First, a high-precision rotation estimation method based on normal vector coplanarity constraints that consider the uncertainty of observations is proposed, which can be solved by Levenberg-Marquardt (LM) algorithm efficiently.
no code implementations • 15 Jun 2023 • Jianzhu Huai, Yuan Zhuang, Yuxin Shao, Grzegorz Jozkow, Binliang Wang, Yijia He, Alper Yilmaz
These tests reveal the strengths and weaknesses of these camera models, as well as the repeatability of these GCC tools.
1 code implementation • CVPR 2023 • Yijia He, Bo Xu, Zhanpeng Ouyang, Hongdong Li
We propose a novel visual-inertial odometry (VIO) initialization method, which decouples rotation and translation estimation, and achieves higher efficiency and better robustness.
1 code implementation • 15 Apr 2022 • XiaoFeng Wang, Zheng Zhu, Fangbo Qin, Yun Ye, Guan Huang, Xu Chi, Yijia He, Xingang Wang
Therefore, we present MVSTER, which leverages the proposed epipolar Transformer to learn both 2D semantics and 3D spatial associations efficiently.
no code implementations • ICCV 2021 • Haotian Zhang, Yicheng Luo, Fangbo Qin, Yijia He, Xiao Liu
The line description ability of ELSD also outperforms the previous works on the line matching task.
Ranked #1 on Line Segment Detection on wireframe dataset
no code implementations • 20 Jan 2021 • Xingyin Fu, Zheng Fang, Xizhen Xiao, Yijia He, Xiao Liu
In this paper, we propose an improved Signed Distance Function (SDF) for both 2D SLAM and pure localization to improve the accuracy of mapping and localization.
1 code implementation • 16 Sep 2020 • Qiang Fu, Jialong Wang, Hongshan Yu, Islam Ali, Feng Guo, Yijia He, Hong Zhang
This paper presents PL-VINS, a real-time optimization-based monocular VINS method with point and line features, developed based on the state-of-the-art point-based VINS-Mono \cite{vins}.
2 code implementations • ECCV 2020 • Siyu Huang, Fangbo Qin, Pengfei Xiong, Ning Ding, Yijia He, Xiao Liu
To realize one-step detection with a faster and more compact model, we introduce the tri-points representation, converting the line segment detection to the end-to-end prediction of a root-point and two endpoints for each line segment.
Ranked #2 on Line Segment Detection on York Urban Dataset
1 code implementation • 30 Apr 2020 • Baichuan Huang, Hongwei Yi, Can Huang, Yijia He, Jingbin Liu, Xiao Liu
To improve the robustness and completeness of point cloud reconstruction, we propose a novel multi-metric loss function that combines pixel-wise and feature-wise loss function to learn the inherent constraints from different perspectives of matching correspondences.
1 code implementation • 21 Apr 2020 • Baichuan Huang, Hongwei Yi, Can Huang, Yijia He, Jingbin Liu, Xiao Liu
To improve the robustness and completeness of point cloud reconstruction, we propose a novel multi-metric loss function that combines pixel-wise and feature-wise loss function to learn the inherent constraints from different perspectives of matching correspondences.
no code implementations • 16 Apr 2020 • Xin Li, Yijia He, Jinlong Lin, Xiao Liu
To improve the accuracy of 3D mesh generation and localization, we propose a tightly-coupled monocular VIO system, PLP-VIO, which exploits point features and line features as well as plane regularities.
no code implementations • 11 Oct 2019 • Ziwei Liao, Jieqi Shi, Xianyu Qi, Xiao-Yu Zhang, Wei Wang, Yijia He, Ran Wei, Xiao Liu
Robust visual localization for urban vehicles remains challenging and unsolved.