activity
20192021
most citedSelf-Supervised Deep Visual Odometry with Online Adaptation

5 citations · 7 across the 3 of their papers we have counts for

collaborators

6 papers

cs.CV2021

Continual Neural Mapping: Learning An Implicit Scene Representation from Sequential Observations

Zike Yan, Yuxin Tian, Xuesong Shi +3

Recent advances have enabled a single neural network to serve as an implicit scene representation, establishing the mapping function between spatial coordinates and scene propertie…

cs.CV20212 cited

Online Learning of a Probabilistic and Adaptive Scene Representation

Zike Yan, Xin Wang, Hongbin Zha

Constructing and maintaining a consistent scene model on-the-fly is the core task for online spatial perception, interpretation, and action. In this paper, we represent the scene w…

cs.CV2020

Line Flow based SLAM

Qiuyuan Wang, Zike Yan, Junqiu Wang +3

We propose a visual SLAM method by predicting and updating line flows that represent sequential 2D projections of 3D line segments. While feature-based SLAM methods have achieved e…

cs.CV20205 cited

Self-Supervised Deep Visual Odometry with Online Adaptation

Shunkai Li, Xin Wang, Yingdian Cao +3

Self-supervised VO methods have shown great success in jointly estimating camera pose and depth from videos. However, like most data-driven methods, existing VO networks suffer fro…

cs.CV2019

Sequential Adversarial Learning for Self-Supervised Deep Visual Odometry

Shunkai Li, Fei Xue, Xin Wang +2

We propose a self-supervised learning framework for visual odometry (VO) that incorporates correlation of consecutive frames and takes advantage of adversarial learning. Previous m…

cs.CV2019

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…