14 citations · 15 across the 2 of their papers we have counts for
4 papers
Deep Visual Odometry with Adaptive Memory
Fei Xue, Xin Wang, Junqiu Wang +1
We propose a novel deep visual odometry (VO) method that considers global information by selecting memory and refining poses. Existing learning-based methods take the VO task as a…
Local Supports Global: Deep Camera Relocalization with Sequence Enhancement
Fei Xue, Xin Wang, Zike Yan +3
We propose to leverage the local information in image sequences to support global camera relocalization. In contrast to previous methods that regress global poses from single image…
Beyond Tracking: Selecting Memory and Refining Poses for Deep Visual Odometry
Fei Xue, Xin Wang, Shunkai Li +3
Most previous learning-based visual odometry (VO) methods take VO as a pure tracking problem. In contrast, we present a VO framework by incorporating two additional components call…
Guided Feature Selection for Deep Visual Odometry
Fei Xue, Qiuyuan Wang, Xin Wang +3
We present a novel end-to-end visual odometry architecture with guided feature selection based on deep convolutional recurrent neural networks. Different from current monocular vis…