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Yusuke Matsui

Lecturer (Assistant Professor)

Department of Information and Communication Engineering, Graduate School of Information Science and Technology, The University of Tokyo, Japan

I am a Lecturer (Assistant Professor) at the University of Tokyo, Japan. My main research areas are computer vision, data structures, and machine learning. I specialize in two areas: (1) developing algorithms and systems for large-scale data indexing and (2) creating learning-enhanced data structures that combine machine learning with traditional data structures.

Aizawa Yamakata Matsui Laboratory, Department of Information and Communication Engineering, the University of Tokyo, Fac. of Eng. Bldg. #2, 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
matsui(at)hal.t.u-tokyo.ac.jp

Members

  • Yingxuan Li (D1)
  • Yusuke Kondo (D1)
  • Yanyuan Fu (M2)
  • Tomohiro Kanaumi (M2)
  • Ryotaro Kako (M2)
  • Hiroki Azuma (M1)
  • Atsuki Sato (M1)
  • Kunato Nishina (M1)
  • Ryoya Nara (B4)
  • Fuma Hidaka (B4)
  • Yutaro Oguri (B4)
  • Hayate Masuda (B4)
  • Takuto Onikubo (B4)

  • Naoki Ono (B:2020-2021, M:2021-2023)
  • Riku Yamashita (M:2021-2023)
  • Haruka Kumagai (B:2022-2023)
  • Misaki Ohashi (B:2021-2022)
  • Kishin Matsuoka (B:2021-2022)
  • Yoichiro Hisadome (B:2020-2021)

News

Lectures

  • Non-Research Tips for Information Science Researchers (2024)
  • Media Computing in Practice (2022)

Tips

Projects

High-Performance Data Science

Yusuke Matsui, Daichi Amagata, Hiroaki Shiokawa, and Mai Nishimura
AIP Acceleration Research

Project

Neural Search in Action

Yusuke Matsui, Martin Aumüller, and Han Xiao
CVPR 2023 Tutorial

Tutorial

ARM 4-bit PQ

Yusuke Matsui, Yoshiki Imaizumi, Naoya Miyamoto, and Naoki Yoshifuji
ICASSP 2022
Implemented in Faiss: issue, PR

Paper Blog by Imaizumi Blog by Matsui

Image Retrieval in the Wild

Yusuke Matsui, Takuma Yamaguchi, and Zheng Wang
CVPR 2020 Tutorial

Tutorial

Reconfigurable Inverted Index

Yusuke Matsui, Ryota Hinami, and Shin'ichi Satoh
ACMMM 2018 (oral, acceptance rate: 8.45%)

Paper Project Code Slides Poster

A Survey of Product Quantization

Yusuke Matsui, Yusuke Uchida, Hervé Jégou, and Shin'ichi Satoh
ITE Transactions on Media Technology and Applications 2018

Paper Project

PQk-means: Billion-scale Clustering for Product-quantized Codes

Yusuke Matsui*, Keisuke Ogaki*, Toshihiko Yamasaki, and Kiyoharu Aizawa *Joint first authors.
ACMMM 2017

Paper Project Code News release

PQTable: Nonexhaustive Fast Search for Product-Quantized Codes Using Hash Tables

Yusuke Matsui, Toshihiko Yamasaki, and Kiyoharu Aizawa
ICCV 2015, TMM 2018

Paper Project Code

Writing an Image Search Engine from Scratch

Yusuke Matsui
One-hour hands-on seminar at CGVI, 2017
Image Retrieval in the Wild, CVPR Tutorial, 2020

Project Slide Slide (Jp) Code Demo Video

DrawFromDrawings: 2D Drawing Assistance via Stroke Interpolation with a Sketch Database

Yusuke Matsui, Takaaki Shiratori, and Kiyoharu Aizawa
IEEE Transactions on Visualization and Computer Graphics (TVCG), 2017

Paper Project Video

Sketch-based Manga Retrieval using Manga109 Dataset

Yusuke Matsui, Kota Ito, Yuji Aramaki, Azuma Fujimoto, Toru Ogawa, Toshihiko Yamasaki, and Kiyoharu Aizawa
Multimedia Tools and Applications (MTAP), Springer, 2017

Paper Project

Illustration2Vec: A Semantic Vector Representation of Illustrations

Masaki Saito and Yusuke Matsui
ACM SIGGRAPH Asia, Technical Brief, 2015

Paper Project

Separation of Manga Line Drawing and Screentones

Kota Ito, Yusuke Matsui, Toshihiko Yamasaki, and Kiyoharu Aizawa
Eurographics, Short paper, 2015

Code

Reference-based Manga Colorization by Graph Correspondence Using Quadratic Programming

Kazuhiro Sato, Yusuke Matsui, Toshihiko Yamasaki, and Kiyoharu Aizawa
ACM SIGGRAPH Asia, Technical Briefs, 2014

Paper

Publications

Journal

Conference

Technical report

Tutorial

Codes

  • annbench: Simple and lightweight benchmark for approximate nearest neighbor search in python
  • manga109api: Simple python API to read annotation data of Manga109
  • Rii: Fast and memory-efficient ANN with a subset-search functionality
  • nanopq: Pure python implementation of product quantization for nearest neighbor search
  • PQk-means: Fast and memory-efficient clustering
  • faiss_tips: Some useful tips for faiss
  • PQTable: Fast search algorithm for product-quantized codes via hash-tables
  • Simple image search engine
  • Manga109: A dataset of manga (Japanese comics)

Last updated: March 23, 2023