142 citations · 272 across the 6 of their papers we have counts for
8 papers
Online Temporal Fusion for Vectorized Map Construction in Mapless Autonomous Driving
Jiagang Chen, Liangliang Pan, Shunping Ji +2
To reduce the reliance on high-definition (HD) maps, a growing trend in autonomous driving is leveraging onboard sensors to generate vectorized maps online. However, current method…
Fisher Information Field: an Efficient and Differentiable Map for Perception-aware Planning
Zichao Zhang, Davide Scaramuzza
Considering visual localization accuracy at the planning time gives preference to robot motion that can be better localized and thus has the potential of improving vision-based nav…
Reference Pose Generation for Long-term Visual Localization via Learned Features and View Synthesis
Zichao Zhang, Torsten Sattler, Davide Scaramuzza
Visual Localization is one of the key enabling technologies for autonomous driving and augmented reality. High quality datasets with accurate 6 Degree-of-Freedom (DoF) reference po…
Voxel Map for Visual SLAM
Manasi Muglikar, Zichao Zhang, Davide Scaramuzza
In modern visual SLAM systems, it is a standard practice to retrieve potential candidate map points from overlapping keyframes for further feature matching or direct tracking. In t…
Redesigning SLAM for Arbitrary Multi-Camera Systems
Juichung Kuo, Manasi Muglikar, Zichao Zhang +1
Adding more cameras to SLAM systems improves robustness and accuracy but complicates the design of the visual front-end significantly. Thus, most systems in the literature are tail…
Visual-Inertial Odometry of Aerial Robots
Davide Scaramuzza, Zichao Zhang
Visual-Inertial odometry (VIO) is the process of estimating the state (pose and velocity) of an agent (e.g., an aerial robot) by using only the input of one or more cameras plus on…
Rethinking Trajectory Evaluation for SLAM: a Probabilistic, Continuous-Time Approach
Zichao Zhang, Davide Scaramuzza
Despite the existence of different error metrics for trajectory evaluation in SLAM, their theoretical justifications and connections are rarely studied, and few methods handle temp…
Learning-based Image Enhancement for Visual Odometry in Challenging HDR Environments
Ruben Gomez-Ojeda, Zichao Zhang, Javier Gonzalez-Jimenez +1
One of the main open challenges in visual odometry (VO) is the robustness to difficult illumination conditions or high dynamic range (HDR) environments. The main difficulties in th…