Meng Cao
3rd Year M.Sc. Student @ Peking University
Email: mengcao@pku.edu.cn
Github: https://github.com/rookiecm
Resume: CV
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About me
About me
I'm currently a third-year M.Sc. student in School of Electronic and Computer Engineering, Peking University (PKU), advised by Prof. Yuexian Zou. Before that in 2018, I received my B.Sc. degree in School of Hydropower and Information Engineering in Huazhong University of Science and Technology (HUST), where I am fortunate enough to work with Prof. Chaoshun Li.
My research interests lay in Computer Vision and Computer Graphics, especially in :
(1) Natural Language Video Localization.
(2) face and scene generation from 3D perspective.
(3) Scene Text Detection.
News
News
[Aug. 2021] One paper is accepted by EMNLP-2021. Coming soon.
[June. 2021] One paper is accepted by IEEE-TIP .
[Mar. 2021] One paper is accepted by CVPR 2021 .
[Mar. 2021] One paper is accepted by IEEE-TCSVT .
Preprints
Preprints
Publications
Publications
All you need is a second look: Towards tighter arbitrary shape text detection
Meng Cao, Yuexian Zou.
IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2020)
GISCA: Gradient-Inductive Segmentation Network With Contextual Attention for Scene Text Detection
Meng Cao, Yuexian Zou, Dongming Yang, Chao Liu
IEEE Access
Experiences
Experiences
Tencent AI Lab Research intern Jul 2019 - Aug 2020
A Unified Framework for Video Portrait Manipulation: We conduct a 3D-based framework for general video portrait manipulations including face swapping, face reenactment and other applications.
Alibaba Group Software engineering intern Mar 2018 - Aug 2018
Unbalanced sample training: For the actual corpus, the unbalanced sampling algorithm Borderline-SMOTE is used. The training model is adjusted using fastText toolbox to realize the search recall sorting algorithm.
Qihoo 360 Software engineering intern Nov 2017 - Jan 2018
Malicious domain name detection: Based on the characteristics of the DGA malicious domain name generation algorithm, LSTM is used to detect hidden malicious domain names.
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