Xinyu Wang

Orcid: 0000-0001-9082-094X

Affiliations:
  • University of Adelaide, Australian Institute for Machine Learning (AIML), SA, Australia
  • Jiangxi Normal University, School of Computer and Information Engineering, Nanchang, China (former)


According to our database1, Xinyu Wang authored at least 13 papers between 2017 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

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PhD thesis 
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Links

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Bibliography

2024
When IC meets text: Towards a rich annotated integrated circuit text dataset.
Pattern Recognit., March, 2024

Improving Handwritten Mathematical Expression Recognition via Similar Symbol Distinguishing.
IEEE Trans. Multim., 2024

2023
SPTS v2: Single-Point Scene Text Spotting.
IEEE Trans. Pattern Anal. Mach. Intell., December, 2023

2022
SPTS: Single-Point Text Spotting.
Proceedings of the MM '22: The 30th ACM International Conference on Multimedia, Lisboa, Portugal, October 10, 2022

2021
Exploring the Capacity of an Orderless Box Discretization Network for Multi-orientation Scene Text Detection.
Int. J. Comput. Vis., 2021

SPTS: Single-Point Text Spotting.
CoRR, 2021

ICDAR 2021 Competition on Integrated Circuit Text Spotting and Aesthetic Assessment.
Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021

2020
Human Detection Aided by Deeply Learned Semantic Masks.
IEEE Trans. Circuits Syst. Video Technol., 2020

On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering.
Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019
Real-Time Deep Tracking via Corrective Domain Adaptation.
IEEE Trans. Circuits Syst. Video Technol., 2019

Exploring the Capacity of Sequential-free Box Discretization Network for Omnidirectional Scene Text Detection.
CoRR, 2019

2017
Robust and real-time deep tracking via multi-scale domain adaptation.
Proceedings of the 2017 IEEE International Conference on Multimedia and Expo, 2017

Deep tracking with objectness.
Proceedings of the 2017 IEEE International Conference on Image Processing, 2017


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