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ICCV is the premier international computer vision event comprising the main conference and several co-located workshops and tutorials.

October 11 ~ 17, 2021
(ICCV-2021 is a Virtual-only Conference)

It is Sony's pleasure to become a Champion Exhibitor of ICCV-2021.

Recruit information for ICCV-2021

We look forward to highly motivated individuals applying to Sony so that we can work together to fill the world with emotion and pioneer the future with dreams and curiosity. Join us and be part of a diverse, innovative, creative, and original team to inspire the world. If you are interested in working with us, please click here for more open positions of job and internship.

  • Lead Research Scientist Machine Learning for Gastronomy

    Full Time
    Tokyo, Japan
    Machine Learning

  • Project Lead - AI Ethics: AI Ethics Office (AEO), Sony Group Corporation

    Full Time
    Tokyo, Japan
    Others

  • Project Manager

    Full Time
    Tokyo, Japan
    Others

  • Research Scientist (Ethics)

    Full Time
    Tokyo, Japan
    AI Ethics

  • Robotics Engineer

    Full Time
    Tokyo, Japan
    Robotics

  • Senior Research Scientist (Computer Vision)

    Full Time
    Tokyo, Japan
    Computer Vision

  • Senior Research Scientist (Reinforcement Learning)

    Full Time
    Tokyo, Japan
    Reinforcement Learning

  • Senior Research Scientist (Robotics)

    Full Time
    Tokyo, Japan
    Robotics

  • AI Engineer

    Full Time
    United States
    Machine Learning

  • Research Scientist (Computer Vision and Algorithmic Fairness)

    Full Time
    United States
    AI Ethics / Computer Vision

  • Research Scientist (Reinforcement Learning)

    Full Time
    United States
    Reinforcement Learning

  • Senior Research Scientist (Reinforcement Learning)

    Full Time
    United States
    Reinforcement Learning

  • AI Application Engineer

    Full Time
    Tokyo, Japan
    Computer Vision / Natural Language Processing

  • Computational Photography, Next Generation Image Sensing Technology Researcher

    Full Time
    Tokyo, Japan
    Computer Vision

  • AI Application Engineer

    Internship
    Tokyo, Japan
    Computer Vision / Natural Language Processing

  • Computational Photography, Next Generation Image Sensing Technology Researcher

    Internship
    Tokyo, Japan
    Computer Vision

  • Deep Learning, Researcher/Research Engineer/Software Engineer

    Internship
    Tokyo, Japan
    Machine Learning

  • Machine Learning & Computer Vision, Software Engineer

    Internship
    Tokyo, Japan
    Computer Vision

  • Senior Research Engineer - Machine Learning/Image Processing

    Full Time
    San Jose, United States
    Computer Vision / Machine Learning

  • Senior Research Engineer Biomedical Engineering & Computer Vision

    Full Time
    San Jose, United States
    Machine Learning / Data Analysis

  • Research Engineer | Computational Sensing, Embedded AI

    Full Time
    Tokyo, Japan
    Computer Vision

  • Senior Computer Vision / AI / Data Science Engineer

    Full Time
    Zurich, Switzerland
    Machine Learning / Computer Vision

  • Senior Research Scientist

    Full Time
    Mumbai or Bangalore, India
    Machine Learning / Data Analysis

  • Next Generation AI/Machine Learning Senior Research Scientist

    Full Time
    San Mateo, United States
    Computer Vision / Machine Learning

Our event information

Sponsor Session 01

(1) Federated Learning in Practice

on-demand

Federated Learning has attracted significant attentions since it offers a privacy-aware model training paradigm which does not require raw data sharing but allows participants to collaboratively construct a better global model. In this talk, I will introduce the background and categorization of Federated Learning, followed by several interesting industrial cases.

  • Speaker :

    Lingjuan Lyu - Sony AI

(2) Visual Datasets and Biases

on-demand

Machine learning models invariably depend on the source of their experience-i.e., the data that they are trained and evaluated on. Data size and efficiency are often prioritised to the detriment of data curation practices. In this talk, I will overview several research questions related to visual datasets and biases.

  • Speaker :

    Jerone Andrews - Sony AI

Sponsor Session 02

Highly Efficient Realtime Visual Sensing Applications with Event-based Sensors

on-demand

Inspired by human eyes, event-based vision sensors (EVS) are an emerging technology that addresses challenging scenarios faced by today's conventional cameras. They react quickly to sudden changes, handle extreme lighting conditions and operate with very little power. We have drastically reduced the EVS pixel and reached a size where we can integrate it with state-of-the art image sensors to get the best of both worlds. We are developing software solutions to facilitate adaptation of the EVS technology in various markets. We introduce some of our current works including high-speed tracking, high-speed depth sensing, visual light communication and efficient event-based processing.

  • Speaker :

    Yoshitaka Miyatani - Sony Semiconductor Solutions Corporation, Japan

Sponsor Session 03

(1) Densely connected multidilated convolutional networks for dense prediction tasks

on-demand

Tasks such as semantic segmentation require a modeling of both local and global structures in a large input field. As the local and global structures often depend on each other, their simultaneous modeling is important. We propose a novel CNN architecture called D3Net that enables multiresolution learning in almost all layers. D3Net outperforms SOTA architectures in several tasks.

  • Speaker :

    Naoya Takahashi - R&D Center, Sony Group Corporation

(2) Beyond image recognition towards audio and language

on-demand

Multimodal recognition is critical for realizing AI that understands the world at a deeper level. We introduce some of Sony's endeavors towards such goal, first with localization of sounding objects through weakly supervised learning, and also with a review of transformer architecture in visuolinguistic tasks.

  • Speaker :

    Tokuhiro Nishikawa - R&D Center, Sony Group Corporation

  • Speaker :

    Andrew Shin - R&D Center, Sony Group Corporation

Technologies & Business
use case

Technology 02

Sony's Latest Image Sensors and the Technologies that Lies Behind Them

In the imaging and sensing field, Sony has a great selection of cutting-edge products, such as intelligent vision sensors with AI processing functionality, ToF image sensors that can be used even for AR/MR, and automotive image sensors critical to realizing autonomous driving. The unique technologies that lie behind these products are all world firsts, and include back-illuminated CMOS image sensors, stacked CMOS image sensors, and Cu-Cu direct bonding.

Technology 03

Imaging and Sensing Technology

CMOS image sensor development at Sony began in 1996 and led to the launch of our first CMOS image sensor (IMX001) in 2000. At the time, CMOS image sensors produced noisy images under low light and were also inferior to CCD image sensors in the number of pixels. However, the lower readout speed of CCD image sensors convinced us that they would be unable to support high-resolution data as the industry moved from SD to HD video. In 2004, we therefore changed course greatly by shifting our focus from CCD to CMOS image sensor development. It was a bold decision. Instead of holding the world's number one share in CCD image sensors, we would be building on a negligible market share in CMOS image sensors.
Later in 2007 we commercialized CMOS image sensors with an original column A/D conversion circuit for fast, low-noise performance, followed in 2009 by back-illuminated CMOS image sensors with twice the sensitivity of conventional image sensors – beyond the human eye.
Further examples of technical innovation that has enabled us to constantly lead the industry include stacked CMOS image sensors in 2012 – with higher image quality and multiple functions in a smaller package, thanks to layering of the pixel and signal-processing sections – and, in 2015, the world's first image sensors with a Cu-Cu connection, enabling smaller packages, higher performance, and greater productivity in manufacturing.

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