147 citations · 181 across the 3 of their papers we have counts for
6 papers
BALF: Simple and Efficient Blur Aware Local Feature Detector
Zhenjun Zhao, Yu Zhai, Ben M. Chen +1
Local feature detection is a key ingredient of many image processing and computer vision applications, such as visual odometry and localization. Most existing algorithms focus on f…
MBA-VO: Motion Blur Aware Visual Odometry
Peidong Liu, Xingxing Zuo, Viktor Larsson +1
Motion blur is one of the major challenges remaining for visual odometry methods. In low-light conditions where longer exposure times are necessary, motion blur can appear even for…
Self-Supervised Linear Motion Deblurring
Peidong Liu, Joel Janai, Marc Pollefeys +2
Motion blurry images challenge many computer vision algorithms, e.g, feature detection, motion estimation, or object recognition. Deep convolutional neural networks are state-of-th…
Robust Dense Mapping for Large-Scale Dynamic Environments
Ioan Andrei Bârsan, Peidong Liu, Marc Pollefeys +1
We present a stereo-based dense mapping algorithm for large-scale dynamic urban environments. In contrast to other existing methods, we simultaneously reconstruct the static backgr…
Efficient 2D-3D Matching for Multi-Camera Visual Localization
Marcel Geppert, Peidong Liu, Zhaopeng Cui +2
Visual localization, i.e., determining the position and orientation of a vehicle with respect to a map, is a key problem in autonomous driving. We present a multicamera visual iner…
Project AutoVision: Localization and 3D Scene Perception for an Autonomous Vehicle with a Multi-Camera System
Lionel Heng, Benjamin Choi, Zhaopeng Cui +10
Project AutoVision aims to develop localization and 3D scene perception capabilities for a self-driving vehicle. Such capabilities will enable autonomous navigation in urban and ru…