VISION PROGRAM

Provide a frictionless image based experience using advanced computer vision research

The mission of vision group, a part of Rakuten Institute of Technology, is to use advanced computer vision research for automation and new service creation. This group consists of several experienced PhD researchers specializing in computer vision domain and motivated to use their research knowledge for driving innovation at Rakuten.

Focus areas include initiatives such as developing an accurate and scalable eKYC (electronic Know Your Customer) solution using optical character recognition and face authentication to improve customer experience by drastically reducing time taken for customer onboarding, generating creative AI solutions to improve the aesthetic quality and conversion rate of advertisements, extracting visual attributes like colors or brands from product images to enrich the product catalog, and analyzing drone-captured images to automate the antenna audits of Rakuten Mobile.

Frictionless experience with images

Images play an essential role for communication in shopping experiences.

Leveraging state-of-the-art computer vision technology, the Vision program builds novel systems to improve such experiences. In addition, pictures such as drivers' licenses are often used in a critical identification process called Know Your Customer (KYC). As one of the largest Fintech companies in Japan, removing friction from identification processes is critical for the customer experience. We are developing robust e-KYC algorithms to address these challenges and create a multi-modal approach combining different types of input data.

PUBLICATIONS

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Action Spotting and Temporal Attention Analysis in Soccer Videos

Conference: MVA 2021

Author: Hiroaki Minoura, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, Mitsuru Nakazawa, Yeongnam Chae, Bjorn Stenger

Publication Year: 2021

Facial Action Unit Detection with Transformers

Conference: CVPR 2021

Author: Geethu Miriam Jacob, Bjorn Stenger

Publication Year: 2021

Seamless Payment System Using Face And Low-Energy Bluetooth

Conference: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops pp.816-817

Author: Lei Yeongnam Chae, Kelvin Cheng, Pankaj Wasnik, Bjorn Stenger

Publication Year: 2020

Content Filtering in Streaming Video Using Domain Adaptation

Conference: MVA 2021

Author: Utsav Shah, Muhammad Rasyid Aqmar, Mitsuru Nakazawa, Bjorn Stenger

Publication Year: 2021

  • Action Spotting and Temporal Attention Analysis in Soccer Videos

    Conference: MVA 2021

    Author: Hiroaki Minoura, Tsubasa Hirakawa, Takayoshi Yamashita, Hironobu Fujiyoshi, Mitsuru Nakazawa, Yeongnam Chae, Bjorn Stenger

    Publication Year: 2021

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CAREERS

We are always looking for great talent and researchers to lead us and work with us.

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