Xi-Yang

Xi Yang (楊 溪)

News

2021.01.09 Our paper has been accepted by ISBI 2021.

2020.09.17 Our paper has been accepted by ACM SIGGRAPH ASIA 2020 Technical Communications.

CV pdf

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Project Assistant Professor
IGARASHI Laboratory
The University of Tokyo

Email: earthyangxi(AT)gmail.com

Education

KONNO Laboratory
Ph.D in Faculty of Engineering from Iwate University, Japan in 2018
ME degree in Faculty of Engineering from Iwate University, Japan in 2015
Zhiyi Zhang
BE degree in College of Information Engineering from Northwest A&F University, China in 2012

Research Interests

Computer graphics
Deep learning
Human–computer interaction

Projects

3D Techniques for Medicine

image Xi Yang, Ding Xia, Taichi Kin, and Takeo Igarashi
IntrA: 3D Intracranial Aneurysm Dataset for Deep Learning
In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2020) Oral


HCL for ML

image Xi Yang, Bojian Wu, Issei Sato, and Takeo Igarashi
Directing DNNs Attention for Facial Attribution Classification using Gradient-weighted Class Activation Mapping
In CVPR Workshops (2019)



Visualization of Lithic Materials

image Xi Yang, Kouichi Konno, Fumito Chiba, Shin Yokoyama
Visualization of Flake Knapping Sequence with Analyzing Assembled Chipped Stone Tools
The Journal of Art and Science (2019)

Xi Yang, Katsutsugu Matsuyama, Kouichi Konno
Interactive Visualization of Assembly Instruction for Stone Tools Restoration
The 10th IEEE Pacific Visualization Symposium (PacificVis 2017)


Matching Lithic Materials

image Xi Yang, Katsutsugu Matsuyama, Kouichi Konno
Pairwise Matching of Stone Tools Based on Flake-Surface Contour Points and Normals
Eurographics Workshop on Graphics and cultural Heritage (GCH 017)


image Xi Yang, Katsutsugu Matsuyama, Kouichi Konno
A New Method of Refitting Mixture Lithic Materials by Geometric Matching of Flake Surfaces
The Journal of Art and Science (2016)


Point Cloud Simplification

image Xi Yang, Katsutsugu Matsuyama, Kouichi Konno, Yoshimasa Tokuyama
A Feature Preserving Simplification of Point Cloud by Using Clustering Approach Based on Mean Curvature
The Journal of Art and Science (2015)



Publications

Preprint

Journal

International Conference

Domestic Conference

Awards

Service

Program Committee

Review

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