Shanyi (Ken) Zhang 张善翌

Final-year undergraduate student in Beihang University, Beijing, China

Research Interest: Computer Vision, Machine Learning, Image Processing

E-mail: zhang_shanyi@qq.com

Address: Xueyuan Road No.37, Haidian District, Beijing, China

[Google Scholar Profile]

DIODE Dataset

Currently I am working on the newly-released DIODE RGB-D Dataset, advised by Prof. Greg Shakhnarovich from Toyota Technological Institute at Chicago.

DIODE (Dense Indoor and Outdoor DEpth) is a dataset that contains diverse high-resolution color images with accurate, dense, wide-range depth measurements. It is the first public dataset to include RGBD images of indoor and outdoor scenes obtained with one sensor suite.

Short Bio

Mr. Shanyi (Ken) Zhang is now a final-year undergraduate student in Beihang University, majoring in Electronic and Information Engineering. His area of focus is 3D Vision Perception and Scene Understanding. During his undergraduate education, he has accumulated research experience both in labs in domestic university and as overseas summer interns. He has been the co-author of several papers in the field of computer vision. He plans to pursue graduate education abroad.


Education

  • Undergraduate (Sep.2016 - Present) | Electronic & Information Engineering | Beihang University
  • Summer School Student (Jul.2017 - Aug.2017) | Information Engineering | University of Illinois at Urbana-Champaign

Publications

[Google Scholar Profile]

  • DIODE: A Dense Indoor and Outdoor DEpth Dataset, I Vasiljevic, N Kolkin, S Zhang, R Luo, H Wang et al, MR Walter, G Shakhnarovich.

In Submission. [PDF]

  • State-of-the-art in 360° Video/Image Processing: Perception, Assessment and Compression, C.Li, M.Xu*, S.Zhang, P.Callet*.

In Submission. [PDF]

  • Deep Complex-valued Neural Network with Learnable Transform for Video Saliency Prediction, L.Jiang, M.Xu*, S.Zhang, L.Sigal*.

In Submission.

  • Viewport Proposal CNN for 360° Video Quality Assessment, C.Li, M.Xu*, L.Jiang, S.Zhang, X.Tao*.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR 2019) [PDF]

Research Experience

  • Lab Member (July.2019 - Present) | New RGB-D Dataset DIODE | Prof.Greg Shakhnarovich | Toyota Technological Institute at Chicago & University of Chicago

Tools: Python, Pytorch, Tensorflow, HTML, Linux Server, Laser Scanner | Related Papers: Depth and normal prediction methods including DORN, DenseDepth etc.


  • Lab Member (Oct.2018 -Jun.2019) | Video Saliency Prediction and Quality Assessment | Prof.Mai Xu | Beihang University

Tools: Python, Tensorflow, Matlab, Linux Server | Related Papers: Saliency prediction methods including Sal-DCNN, DeepVS, Salicon etc.


  • Summer Intern (Jul.2018 - Aug.2018) | Point Cloud Semantic Segmentation for 3D Indoor Scenes | Prof.Gim Hee Lee | National University of Singapore

Tools: Python, Tensorflow, Pytorch, Matlab, Linux Server | Related Papers: Point cloud segmentation methods including PointNet, PointNet++, SPG, PointSIFT etc.


  • Lab Member (Oct.2017 - Jun.2018) | Hardware Deployment of CNN on FPGA | Prof.Guolin Sun | Beihang University

Tools: Python, Tensorflow, Pytorch, Linux Server | Related Papers: Model compression and acceleration methods including BinaryNet, XNOR-Net, Quantized CNN etc.


Work Experience

  • Software Engineering Intern (Jan.2019 - Feb.2019) | BITO Robotics Inc. | Minhang District, Shanghai

Tools: C++, Robot Operating System, Laser Scanner | Project: Real-time point cloud plane extraction


Curriculums

TOEFL: 109 (Speaking: 22)

Overall GPA: 3.7/4.0 [Transcript]

Additional Courses: Neural Network & Deep Learning (Moocs by Andrew Ng), ROS Tutorial (Moocs by CAS)