Bingchen Zhao

This site is deprecated, please visit my new website I am a third year undergrad student major in Computer Science at Tongji University, where I worked closely with Prof. Yin Wang. I started my research internship at Megvii Research Nanjing on Feb 2020, where I worked closely with Dr. Xin Jin.

I open source as much as I can, you can find the code of my work on Github.

Email  /  GitHub  /  Google Scholar   

My research interests include but not limited to

  • Self-Supervised Learning
  • Semi-Supervised Learning
  • Domain Adaptation
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News

         ✩ [Jul. 2020] Our team ranked 2nd in the VIPriors Image Classification challenge ECCV2020.
         ✩ [Jun. 2020] Our team wins the 1st place of iWildCam2020 FGVC7 CVPR2020.
         ✩ [Apr. 2020] I have one paper accepted by APWeb2020 conference.
         ✩ [Apr. 2020] Our team ranked 8th at the 1st Agriculture-Vision Challenge CVPR2020.
         ✩ [Apr. 2020] I have one paper accepted by CVPR2020 workshop proceedings.

Publications

(*) indicates equal contribution.

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Characterizing Robotic and Organic Query in SPARQL Search Sessions


Xinyue Zhang, Meng Wang, Bingchen Zhao, Ruyang Liu, Jingyuan Zhang, Han Yang
The 4th APWeb-WAIM International Joint Conference on Web and Big Data, 2020

We proposed a method for detecting and separating robotic SPARQL queries based on session-level query features.

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Reducing the feature divergence of RGB and near-infrared images using Switchable Normalization


Siwei yang*, Shaozuo Yu*, Bingchen Zhao*, Yin Wang
Proceedings of IEEE CVPR Workshops, 2020
code / slides /

We consider the feature divergence between RGB and NIR channels in agriculture data, switchable norm is used to improve the performance.




Preprints

These paper are still working in progress.

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Context Encoding for Video Retrieval with Contrastive Learning


Jie Shao*, Xin Wen*, Bingchen Zhao, Changhu Wang, Xiangyang Xue
, 2020
arxiv /

We consider the feature divergence between RGB and NIR channels in agriculture data, switchable norm is used to improve the performance.

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Distilling Visual Priors from Self-Supervised Learning


Bingchen Zhao, Xin Wen
, 2020
arxiv / pdf / code / slides /

We present a novel two-phase pipeline that leverages self-supervised learning and knowledge distillation to improve the generalization ability of CNN models for image classification under the data-deficient setting.


Misc


Design and source code from Jon Barron's website