27 citations · 37 across the 3 of their papers we have counts for
6 papers
DF-VO: What Should Be Learnt for Visual Odometry?
Huangying Zhan, Chamara Saroj Weerasekera, Jia-Wang Bian +2
Multi-view geometry-based methods dominate the last few decades in monocular Visual Odometry for their superior performance, while they have been vulnerable to dynamic and low-text…
Diverse Knowledge Distillation for End-to-End Person Search
Xinyu Zhang, Xinlong Wang, Jia-Wang Bian +2
Person search aims to localize and identify a specific person from a gallery of images. Recent methods can be categorized into two groups, i.e., two-step and end-to-end approaches.…
Ordered or Orderless: A Revisit for Video based Person Re-Identification
Le Zhang, Zenglin Shi, Joey Tianyi Zhou +5
Is recurrent network really necessary for learning a good visual representation for video based person re-identification (VPRe-id)? In this paper, we first show that the common pra…
An Evaluation of Feature Matchers for Fundamental Matrix Estimation
Jia-Wang Bian, Yu-Huan Wu, Ji Zhao +4
Matching two images while estimating their relative geometry is a key step in many computer vision applications. For decades, a well-established pipeline, consisting of SIFT, RANSA…
Visual Odometry Revisited: What Should Be Learnt?
Huangying Zhan, Chamara Saroj Weerasekera, Jiawang Bian +1
In this work we present a monocular visual odometry (VO) algorithm which leverages geometry-based methods and deep learning. Most existing VO/SLAM systems with superior performance…
Unsupervised Scale-consistent Depth and Ego-motion Learning from Monocular Video
Jia-Wang Bian, Zhichao Li, Naiyan Wang +4
Recent work has shown that CNN-based depth and ego-motion estimators can be learned using unlabelled monocular videos. However, the performance is limited by unidentified moving ob…