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Jiawang Bian

NTU, ByteDance Seed, MBZUAI, University of Oxford, University of Adelaide

18 papers hereh-index 223.4k citations26 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author5
  • middle author12

Across the 17 of 18 papers where every author was matched, so the position is known.

fields
  • cs.CV18
affiliations
  • NTU, ByteDance Seed, MBZUAI, University of Oxford, University of Adelaide
Homepage
same name
  • Jiawang Bian — 7 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20162024
most citedRicher Convolutional Features for Edge Detection

790 citations · 1.5k across the 18 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CV2019★ 6 cited

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…

cs.CV2019★ 38 cited

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…

cs.CV2019★ 11 cited

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…

cs.CV2019★ 123 cited

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…

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