no code implementations • 17 Jan 2024 • Hao Qu, Lilian Zhang, Jun Mao, Junbo Tie, Xiaofeng He, Xiaoping Hu, Yifei Shi, Changhao Chen
Unreliable feature extraction and matching in handcrafted features undermine the performance of visual SLAM in complex real-world scenarios.
no code implementations • 16 Nov 2022 • Hao Qu, Lilian Zhang, Xiaoping Hu, Xiaofeng He, Xianfei Pan, Changhao Chen
To address this, we propose SelfOdom, a self-supervised dual-network framework that can robustly and consistently learn and generate pose and depth estimates in global scale from monocular images.
1 code implementation • 2 Mar 2021 • Qi Cai, Lilian Zhang, Yuanxin Wu, Wenxian Yu, Dewen Hu
Visual navigation and three-dimensional (3D) scene reconstruction are essential for robotics to interact with the surrounding environment.
no code implementations • 13 Oct 2018 • Qi Cai, Yuanxin Wu, Lilian Zhang, Peike Zhang
The PPO constraints are simplified and formulated in the form of inequalities to directly identify the right pose solution with no need of 3D reconstruction and the 3D reconstruction can be analytically achieved from the identified right pose.